id: https://api.badgr.io/public/badges/mWZXrqjaTOeCGp1bTurQvg
name: R Boot Camp for Ecologists & Wildlife Biologists - PREMIUM
image:
  id: https://api.badgr.io/public/badges/mWZXrqjaTOeCGp1bTurQvg/image
image alt text: R Boot Camp for Ecologists & Wildlife Biologists - PREMIUM badge image
achievement type: Course
description: This badge recognizes the successful completion of the R Boot Camp for Ecologists & Wildlife Biologists. Earners have gained foundational skills in R and RStudio, with a focus on ecological and wildlife-related applications. Skills include importing, cleaning, and transforming ecological datasets, managing relational data, and producing publication-quality data visualizations using ggplot2.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Rstudio
  target url: https://talentneuron.com/
  target description: RStudio is a tailored IDE for R programming, focusing on statistical analysis and data visualization.
  target framework: TALENT_NEURON
  target code: TN-34659
alignment:
  target name: R Programming Language
  target url: https://talentneuron.com/
  target description: R Programming Language is an open-source platform for statistical computing and graphics, enabling data manipulation, calculation, and graphical display.
  target framework: TALENT_NEURON
  target code: TN-33897
alignment:
  target name: Data cleaning
  target url: https://talentneuron.com/
  target description: Data cleaning refers to the process of detecting and correcting errors, inconsistencies, and inaccuracies in datasets to enhance data quality and reliability for analysis.
  target framework: TALENT_NEURON
  target code: TN-33376
alignment:
  target name: Descriptive statistics
  target url: https://talentneuron.com/
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/r-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all eight modules of the course, including all exercises, which require learners to demonstrate the ability to: - Install and operate R and RStudio - Import, organize, and tidy ecological datasets - Apply R functions to perform descriptive statistics and data transformations - Join and analyze relational datasets - Create and present ecological data visually using _ggplot2_ - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/B_McAbECRA-g6yLs-cLJjA
name: Professional Certificate in Applied Quantitative Ecology
image:
  id: https://badges.parchment.com/public/badges/B_McAbECRA-g6yLs-cLJjA/image
description: Professional Certificate in Applied Quantitative Ecology
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/applied-quantitative-ecology
  narrative: Core Courses: • R Bootcamp for Ecologists & Wildlife Biologists • Research Design • Introduction to Ecological Statistics & Modeling • Generalized Linear, Additive, & Mixed Models • Introduction to Bayesian Modeling in Ecology • Multivariate Ecological Community Analysis (required for plant/community ecologists) Elective Courses (select): • Introduction & Advanced Occupancy Modeling • Capture-Mark-Recapture Techniques • Distance Sampling • Geospatial Modeling (QGIS & R) • Bayesian Hierarchical & Causal Modeling • Python for Biologists • Computer Vision for Ecologists • Model Averaging in Ecology
type: BadgeClass

id: https://api.badgr.io/public/badges/KULz8-SPSYqGBxA6I9Jeog
name: Introduction to Ecological Statistics and Modeling - PREMIUM
image:
  id: https://api.badgr.io/public/badges/KULz8-SPSYqGBxA6I9Jeog/image
description: This badge recognizes successful completion of Introduction to Ecological Statistics and Modeling. Earners gain essential quantitative skills in R to analyze, interpret, and present ecological data for research and publication. Coursework covers data wrangling and visualization, statistical inference for normal populations, nonparametric hypothesis testing, correlation, linear and multiple regression, ANOVA, and model selection. Badge earners can apply statistical reasoning to ecological datasets, interpret outputs, and select appropriate models for their research questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Descriptive statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/46677
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/ecomodel-r
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Import, tidy, and transform ecological datasets in R. - Visualize data clearly using R graphics libraries. - Apply the Central Limit Theorem to sampling distributions. - Calculate confidence intervals, p-values, and perform one- and two-sample t-tests. - Conduct and interpret nonparametric tests (permutation tests, hypothesis testing). - Measure correlation and carry out simple linear regression. - Perform multiple regression with continuous and categorical predictors. - Run ANOVA and interpret results in ecological contexts. - Diagnose multicollinearity, compare competing models, and combine information from multiple models. - Submit exercises demonstrating correct application of statistical analyses to ecological datasets. ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/caNyTxBQRP-ho6RCWXL42A
name: Multivariate Ecological Community Analysis I - PREMIUM
image:
  id: https://api.badgr.io/public/badges/caNyTxBQRP-ho6RCWXL42A/image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis I. Earners can distinguish univariate from multivariate analyses, prepare ecological datasets for multivariate analysis, and select appropriate distance measures based on ecological and statistical properties. Learners gain proficiency in five guided ordination techniques—weighted averaging (WA), polar ordination (PO), canonical correspondence analysis (CCA), redundancy analysis (RDA), and fuzzy set ordination (FSO)—and learn how to interpret ordination diagrams. Coursework includes hands-on analysis using PC-ORD software, with optional exercises in R.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Multivariate analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47175
  target description: Multivariate analysis is a statistical method that examines the connections between numerous variables and their combined effect on the results being investigated.
  target framework: TALENT_NEURON
  target code: TN-47175
alignment:
  target name: Multivariate statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/39779
  target description: Multivariate statistics are techniques for analyzing data with multiple variables, revealing patterns and relationships beyond what univariate or bivariate analysis can detect.
  target framework: TALENT_NEURON
  target code: TN-39779
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/meca-i
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, assignments, and required surveys. - Demonstrate the ability to: - Distinguish between univariate and multivariate analyses. - Match dataset properties to appropriate distance measures. - Organize ecological data into matrices suitable for multivariate analysis. - Recognize when and how to modify data prior to analysis. - Set up and conduct analyses using WA, PO, CCA, RDA, and FSO. - Interpret analysis outputs and present ordination diagrams. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/lYGIe2BJQoCrFlU13pUGnA
name: Generalized Linear, Additive, & Mixed Models - PREMIUM
image:
  id: https://api.badgr.io/public/badges/lYGIe2BJQoCrFlU13pUGnA/image
achievement type: Course
description: This badge recognizes successful completion of Generalized Linear, Additive, & Mixed Models. Earners gain skills to analyze ecological data in R, including counts, proportions, and continuous measurements. They learn to fit and interpret generalized linear models (GLMs), extend them to address overdispersion and zero-inflation, and apply generalized additive models (GAMs) for flexible, non-linear relationships. The course also covers repeated measurements, profile analysis, and the use of fixed vs. random effects in mixed models. Learners practice residual diagnostics, model-checking, and model comparison/averaging using AIC, enabling them to build robust statistical models for ecological and wildlife applications.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/generalized-linear-models
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify and apply appropriate GLMs (Poisson, binomial, extensions) for ecological data. - Address overdispersion and zero-inflation in model fitting. - Fit generalized additive models (GAMs) to capture non-linear ecological relationships. - Perform model-checking and residual diagnostics in R. - Compare and average models using AIC. - Analyze repeated measurements data and conduct profile analysis. - Distinguish between fixed and random effects and fit mixed models accordingly. - Submit exercises demonstrating application of GLMs, GAMs, or mixed models to ecological datasets. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/YTpCHj_FSfeNI90liAdqmQ
name: Research Design - PREMIUM
image:
  id: https://api.badgr.io/public/badges/YTpCHj_FSfeNI90liAdqmQ/image
description: This badge recognizes successful completion of the Research Design course. Earners can plan rigorous ecological and wildlife research studies by selecting and applying appropriate sampling techniques (systematic, random, stratified, multi-stage, mark-recapture, distance sampling) and experimental design methods (randomization, replication, blocking, BACI, factorial treatments, covariates). They are able to evaluate validity, minimize bias, and perform power and precision analyses in R to determine appropriate sample sizes and study feasibility.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Experimental design
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/19508
  target description: Experimental design refers to the planning and organization of scientific tests to examine hypotheses, ensuring credible and consistent outcomes through controlled, randomized, and repeatable methods.
  target framework: TALENT_NEURON
  target code: TN-19508
alignment:
  target name: Observational studies
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47206
  target description: Observational studies involve gathering data by monitoring subjects in their natural or controlled environments without interfering with the setting or participants.
  target framework: TALENT_NEURON
  target code: TN-47206
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/research-design
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Define research objectives and assess spatial, temporal, and sampling variability. - Apply appropriate sampling strategies (systematic, random, stratified, multi-stage, mark-recapture, distance sampling). - Identify and minimize sources of bias, error, and pseudo-replication. - Design experiments incorporating randomization, replication, blocking, BACI designs, factorial treatments, and covariates. - Evaluate internal and external validity in ecological study designs. - Perform power and precision analyses in R to calculate required sample sizes and assess study feasibility. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/y3X2G83ST6aA4-Dnto086A
name: Introduction to Bayesian Modeling in Ecology - PREMIUM
image:
  id: https://api.badgr.io/public/badges/y3X2G83ST6aA4-Dnto086A/image
achievement type: Course
description: This badge recognizes successful completion of Introduction to Bayesian Modeling in Ecology. Earners develop foundational knowledge of Bayesian statistics and their application in ecology and wildlife management. Skills include specifying prior and likelihood distributions, applying Bayes’ Rule, and fitting normal, generalized linear, and hierarchical Bayesian models in R using the rjags package. Learners also gain experience with Markov chain Monte Carlo (MCMC) methods, model checking, model comparison, and effectively presenting Bayesian results.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Bayesian analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/35947
  target description: Bayesian analysis is a statistical method based on Bayes' theorem that updates the likelihood of a hypothesis when new data or evidence is introduced.
  target framework: TALENT_NEURON
  target code: TN-35947
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-statistics
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain the advantages and disadvantages of the Bayesian approach. - Specify prior and likelihood distributions and apply Bayes’ Rule to obtain posterior distributions. - Implement Bayesian models in R using the _rjags_ package. - Fit Bayesian normal, generalized linear, and hierarchical models. - Apply Markov chain Monte Carlo (MCMC) methods for model estimation. - Conduct Bayesian model checking and comparison. - Clearly interpret and communicate results from Bayesian analyses. - Submit assignments demonstrating correct implementation and interpretation of Bayesian models in R. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/GtmnVK3aSxGCEOLdM7Rltw
name: Python Boot Camp for Ecologists & Wildlife Biologists - PREMIUM
image:
  id: https://api.badgr.io/public/badges/GtmnVK3aSxGCEOLdM7Rltw/image
description: This badge recognizes successful completion of the Python Boot Camp for Ecologists & Wildlife Biologists. Earners develop foundational coding skills in Python, with applications to data wrangling, visualization, and introductory machine learning. Coursework covers Python installation, programming fundamentals, Jupyter notebooks, the Pandas library for data manipulation, and scikit-learn for basic modeling. Badge earners can use Python interactively to import, clean, and analyze ecological datasets, create plots, and begin applying machine learning techniques.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Python
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18349
  target description: Python is a versatile, high-level language, prioritizing readability and ease, with extensive libraries, commonly utilized for web development, data analysis, AI, and scripting tasks.
  target framework: TALENT_NEURON
  target code: TN-18349
alignment:
  target name: Programming languages
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/44964
  target description: Programming languages are structured computer languages used to convey instructions to machines, primarily computers, for creating executable programs to perform various tasks and operations.
  target framework: TALENT_NEURON
  target code: TN-44964
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/python-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Install Python and supporting tools (Conda, Jupyter, IDEs). - Write and execute Python code interactively. - Assign variables, manipulate data types, and use functions. - Apply coding fundamentals, including conditionals, loops, and custom functions. - Ingest and manipulate data using Pandas dataframes. - Perform basic data wrangling (reshaping, subsetting, modifying values). - Create visualizations (scatter plots, histograms, basic charts). - Apply introductory machine learning models with scikit-learn. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/mXPFTknjRM-XbVLlFETVYA
name: Distance Sampling - PREMIUM
image:
  id: https://api.badgr.io/public/badges/mXPFTknjRM-XbVLlFETVYA/image
description: This badge recognizes successful completion of Distance Sampling. Earners gain a foundation in designing and implementing distance sampling studies for estimating species abundance and distribution while accounting for imperfect detection. Learners practice unbiased sampling design, data collection, data management, and analysis using the R package unmarked. Skills include applying distance sampling methods with point counts and line transects for solitary and social species, incorporating covariates, and comparing and interpreting models. The course also introduces advanced extensions, including temporal replicates, seasonal data, and Bayesian approaches.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/distance-sampling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify ecological research questions and monitoring priorities for abundance estimation. - Design unbiased population sampling approaches for point counts and line transects. - Explain the importance of detection probability in abundance estimation. - Collect and manage distance sampling field data for analysis. - Implement distance sampling models in R using the *unmarked* package. - Apply distance sampling to solitary species (point counts, line transects) and social species (line transects). - Incorporate covariates on abundance and detection probability to test ecological hypotheses. - Compare models, assess fit, and interpret results. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/CmZXXQhZQ-eMHkzMU6n9eA
name: Model Averaging - PREMIUM
image:
  id: https://api.badgr.io/public/badges/CmZXXQhZQ-eMHkzMU6n9eA/image
description: This badge recognizes successful completion of Model Averaging in Ecology. Earners understand the importance of accounting for both parameter and model uncertainty in ecological data analysis. They gain practical skills in applying Bayesian and frequentist model averaging methods, evaluating when model averaging is appropriate, and interpreting results. Using R, learners conduct point and interval estimation, prediction-based averaging, and implement relevant R packages to produce defensible ecological inferences.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/model-averaging-ecology
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and required surveys. - Demonstrate the ability to: - Explain the need for model averaging and its role in addressing model uncertainty. - Evaluate when model averaging is useful and when it is not appropriate. - Apply Bayesian model averaging techniques, including classical and prediction-based approaches. - Implement frequentist model averaging for point and interval estimation. - Use relevant R packages to code and perform model averaging analyses. - Interpret and clearly describe results obtained from model averaging. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/gO2TiSzLRKuNBLsWVBY78A
name: Multivariate Ecological Community Analysis II - PREMIUM
image:
  id: https://api.badgr.io/public/badges/gO2TiSzLRKuNBLsWVBY78A/image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis II. Earners expand their skills beyond MECA I to apply advanced ordination, classification, group-testing, association, and trait-analysis tools to ecological datasets. Techniques covered include PCA, PCoA, NMS, clustering, MRPP, PerMANOVA, SumF, Indicator Species Analysis (ISA), Mantel Test, Compare Scores, and trait-based analyses such as Functional Diversity and Fourth Corner Analysis. Learners also gain experience in advanced graphing for ordination diagrams, interpreting dendrograms, and applying bootstrapping methods to multivariate analyses.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Multivariate analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47175
  target description: Multivariate analysis is a statistical method that examines the connections between numerous variables and their combined effect on the results being investigated.
  target framework: TALENT_NEURON
  target code: TN-47175
alignment:
  target name: Multivariate statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/39779
  target description: Multivariate statistics are techniques for analyzing data with multiple variables, revealing patterns and relationships beyond what univariate or bivariate analysis can detect.
  target framework: TALENT_NEURON
  target code: TN-39779
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/meca-ii
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, assignments, and required surveys. - Demonstrate the ability to: - Choose and apply advanced ordination methods (PCA, PCoA, NMS, NMS Scores). - Perform agglomerative clustering and select optimal clustering levels. - Apply group-testing procedures (MRPP, blocked MRPP, PerMANOVA, SumF, ISA). - Conduct association assessments (Mantel Test, Compare Scores). - Implement trait-based analyses (Functional Diversity, Fourth Corner Analysis). - Evaluate strengths, weaknesses, and assumptions of multivariate methods. - Interpret analysis outputs and communicate results using advanced graphing tools. - Apply bootstrapping techniques to multivariate analyses (e.g., PerMANOVA). - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/R3n77InFQxqGMlie5qarmg
name: Introduction to Capture-Mark-Recapture - PREMIUM
image:
  id: https://api.badgr.io/public/badges/R3n77InFQxqGMlie5qarmg/image
image alt text: Introduction to Capture-Mark-Recapture - PREMIUM badge image
description: This badge recognizes successful completion of Introduction to Capture-Mark-Recapture. Earners gain a foundation in capture-mark-recapture (CMR) techniques for estimating abundance, density, growth rates, and vital rates in wildlife populations. Skills include linking research questions to study design, applying appropriate sampling methods informed by animal behavior, and analyzing data using MARK and RMark. Learners understand model assumptions, limits, and selection theory, and practice using simulations to improve study design. A case study on grizzly bear population research provides hands-on application of concepts to real-world ecological management questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://talentneuron.com/
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/capture-mark-recapture
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, exercises, and required surveys. - Demonstrate the ability to: - Frame ecological research questions and hypotheses for CMR studies. - Define study populations and identify objectives aligned with population monitoring. - Apply foundations of CMR modeling to detection and non-detection data. - Differentiate among open vs. closed population models, spatial (SECR) vs. non-spatial, and mark-resight approaches. - Incorporate covariates appropriately and recognize their limits. - Link animal behavior, life history, and sampling design to analytical approaches. - Use model selection theory to evaluate assumptions and limitations. - Estimate abundance, density, and growth rates from CMR data. - Earn a C- (70%) or better on the final exam - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/WGSeMAzIQwWJ7Js9Yy_b6Q
name: Bayesian Hierarchical Modeling - PREMIUM
image:
  id: https://api.badgr.io/public/badges/WGSeMAzIQwWJ7Js9Yy_b6Q/image
description: This badge recognizes the successful completion of Bayesian Hierarchical Modeling for Ecologists and Wildlife Biologists. Earners have developed applied skills in fitting, evaluating, and comparing ecological models using a Bayesian hierarchical framework. Skills include distinguishing between observation and ecological processes, fitting spatio-temporal models in R, accounting for spatial and temporal autocorrelation, checking model fit, and assessing predictive performance.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Bayesian analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/35947
  target description: Bayesian analysis is a statistical method based on Bayes' theorem that updates the likelihood of a hypothesis when new data or evidence is introduced.
  target framework: TALENT_NEURON
  target code: TN-35947
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-hierarchical-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Separate observation-process and ecological-process components within a hierarchical model - Identify appropriate observation-process models for various ecological datasets - Fit and interpret spatio-temporal models in R - Evaluate model fit and account for spatial and/or temporal autocorrelation - Compare and interpret competing model structures and predictive ability - Earn a C- (70%) or better on the final assessment - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/XsD6n-9WS7adUGESJ1odmQ
name: Bayesian Causal Networks for Complex Multivariate Systems - PREMIUM
image:
  id: https://api.badgr.io/public/badges/XsD6n-9WS7adUGESJ1odmQ/image
description: This badge recognizes successful completion of Bayesian Causal Networks for Complex Multivariate Systems. Earners develop proficiency in creating, calibrating, and updating Bayesian Causal Network (BCN) models to represent causal relationships in complex ecological systems. Skills include using Netica software to build influence diagrams, decision nets, and Bayesian networks; performing sensitivity analysis; and applying scenario testing to predict system responses. Badge earners can design and refine BCN models to identify leverage points for intervention and support strategic ecological decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Causal Inference
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/58601
  target description: Causal Inference refers to the method of identifying and verifying cause-and-effect connections from observed data, employing statistical models to control for confounding factors and infer causality.
  target framework: TALENT_NEURON
  target code: TN-58601
alignment:
  target name: Causal Analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/63991
  target description: Causal Analysis identifies and evaluates underlying reasons for outcomes, enabling informed decision-making and effective problem-solving strategies.
  target framework: TALENT_NEURON
  target code: TN-63991
alignment:
  target name: Machine learning
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/30919
  target description: Machine learning is a subset of AI concerned with developing systems that learn and enhance through experience, employing algorithms to analyze data, learn from it, and make decisions autonomously.
  target framework: TALENT_NEURON
  target code: TN-30919
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-causal-network-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain Bayesian Causal Network (BCN) concepts and their applications to complex multivariate systems. - Research and document frameworks for BCN modeling relevant to ecological problems. - Create influence diagrams and Decision Nets in Netica. - Build, calibrate, and simplify BCN models. - Conduct sensitivity analysis and scenario testing to assess system behavior. - Update BCN models with new data to refine predictions. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/uk0dYPxiT_-epyQrWP6ZJQ
name: Introduction to Occupancy Modeling - PREMIUM
image:
  id: https://api.badgr.io/public/badges/uk0dYPxiT_-epyQrWP6ZJQ/image
description: This badge recognizes successful completion of Introduction to Occupancy Modeling. Earners learn how to account for imperfect detection when analyzing species presence/absence data, improving the accuracy of ecological inference. Coursework covers single-season occupancy models, incorporating covariates, dealing with missing data, model assumptions, and study design. Learners practice applying Program PRESENCE and RPresence to estimate occupancy and assess model fit while considering sampling unit definition, survey effort allocation, and spatial correlation. Badge earners can design and implement studies of species occurrence that properly account for detection probability.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/occupancy-modeling-intro
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including applied analyses in Program PRESENCE and RPresence. - Demonstrate the ability to: - Explain why accounting for imperfect detection is essential in species occurrence studies. - Apply probability-based methods for estimating occupancy. - Implement single-season occupancy models, with and without covariates. - Handle missing observations and unequal effort in occupancy data. - Assess model assumptions and evaluate model fit. - Estimate occupancy for small areas and finite populations, considering spatial correlation. - Define sampling units, repeat surveys, and allocate effort effectively in study design. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/c8lkG0u8T7CIKD_nT7S6sg
name: Advanced Occupancy Modeling - PREMIUM
image:
  id: https://api.badgr.io/public/badges/c8lkG0u8T7CIKD_nT7S6sg/image
description: This badge recognizes successful completion of Advanced Occupancy Modeling. Earners expand their knowledge of species occurrence modeling by learning multi-scale, multi-state, species co-occurrence, and community-level occupancy approaches. Skills include accounting for correlated detection, false positives, and spatial correlation; implementing dynamic and joint occupancy-habitat dynamics models; and presenting results through plots and species distribution maps in R. Badge earners can design and analyze advanced occupancy studies that provide robust insights into species distributions and community dynamics.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/occupancymodeling-ii
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including advanced analyses in R. - Demonstrate the ability to: - Review and extend static occupancy models with covariates and species distribution mapping. - Apply correlated detection and multi-scale occupancy models. - Account for spatial correlation in occupancy data. - Implement static and dynamic multi-state occupancy models. - Address false positive detections in occupancy studies. - Conduct species co-occurrence and community-level occupancy modeling. - Apply joint occupancy-habitat dynamics models. - Present results using R, including plotting and mapping outputs. - Submit assignments or projects demonstrating correct application and interpretation of advanced occupancy models in ecological research. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/0e428g1iQg6El8zJGVTMxg
name: Species Distribution Modeling - PREMIUM
image:
  id: https://api.badgr.io/public/badges/0e428g1iQg6El8zJGVTMxg/image
description: This badge recognizes the successful completion of Species Distribution Modeling. Earners have developed applied skills to design, fit, evaluate, and interpret species distribution models (SDMs) and ecological niche models (ENMs) using R. Skills include preparing biodiversity and environmental datasets, selecting appropriate modeling frameworks, visualizing and assessing model performance, and applying SDMs to ecological and conservation questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/species-distribution-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Describe the theoretical foundations of species distribution and ecological niche modeling - Evaluate and select appropriate modeling frameworks for different ecological data types and goals - Compile and clean biodiversity and environmental data for SDM and ENM analyses - Fit, visualize, and assess SDMs using R packages and performance metrics - Compare and interpret models based on predictive accuracy and transferability - Apply SDM techniques to ecological and conservation case studies - Earn a C- (70%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final assessment earns 1 credit toward certification (Category F: Modeling and Quantitative Methods) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/w8fI5s0JRCCcjf2uDa1B7Q
name: Badge 1
image:
  id: https://api.badgr.io/public/badges/w8fI5s0JRCCcjf2uDa1B7Q/image
description: Test
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Rstudio
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/34659
  target description: RStudio is a tailored IDE for R programming, focusing on statistical analysis and data visualization.
  target framework: TALENT_NEURON
  target code: TN-34659
criteria:
  narrative: Test
type: BadgeClass

id: https://api.badgr.io/public/badges/Uva5L6emQKGWjkAYp7sDPw
name: Example 1
image:
  id: https://api.badgr.io/public/badges/Uva5L6emQKGWjkAYp7sDPw/image
description: This is an example.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  narrative: Example
type: BadgeClass

id: https://api.badgr.io/public/badges/uGhFQWbtQCaFCctbvwlhkA
name: Example 2
image:
  id: https://api.badgr.io/public/badges/uGhFQWbtQCaFCctbvwlhkA/image
description: Example
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  narrative: Example
type: BadgeClass

id: https://api.badgr.io/public/badges/VvpppkjDT16hUhOMz9SA_Q
name: Example 3
image:
  id: https://api.badgr.io/public/badges/VvpppkjDT16hUhOMz9SA_Q/image
description: Example
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  narrative: Example
type: BadgeClass

id: https://api.badgr.io/public/badges/58ClZe3vRoCTrrFBOPqbtQ
name: Example 4
image:
  id: https://api.badgr.io/public/badges/58ClZe3vRoCTrrFBOPqbtQ/image
description: Example
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  narrative: Example
type: BadgeClass

id: https://api.badgr.io/public/badges/PHjRsmhHTQywGr7xp4GNmw
name: Example Cert
image:
  id: https://api.badgr.io/public/badges/PHjRsmhHTQywGr7xp4GNmw/image
description: Example
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  narrative: Example
type: BadgeClass

id: https://api.badgr.io/public/badges/TrLofCNhS-Kmy_FMiXAl-g
name: R Boot Camp for Ecologists & Wildlife Biologists - BASIC
image:
  id: https://api.badgr.io/public/badges/TrLofCNhS-Kmy_FMiXAl-g/image
image alt text: R Boot Camp for Ecologists & Wildlife Biologists - BASIC badge image
achievement type: Course
description: This badge recognizes the successful completion of the R Boot Camp for Ecologists & Wildlife Biologists. Earners have gained foundational skills in R and RStudio, with a focus on ecological and wildlife-related applications. Skills include importing, cleaning, and transforming ecological datasets, managing relational data, and producing publication-quality data visualizations using ggplot2.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Rstudio
  target url: https://talentneuron.com/
  target description: RStudio is a tailored IDE for R programming, focusing on statistical analysis and data visualization.
  target framework: TALENT_NEURON
  target code: TN-34659
alignment:
  target name: R Programming Language
  target url: https://talentneuron.com/
  target description: R Programming Language is an open-source platform for statistical computing and graphics, enabling data manipulation, calculation, and graphical display.
  target framework: TALENT_NEURON
  target code: TN-33897
alignment:
  target name: Data cleaning
  target url: https://talentneuron.com/
  target description: Data cleaning refers to the process of detecting and correcting errors, inconsistencies, and inaccuracies in datasets to enhance data quality and reliability for analysis.
  target framework: TALENT_NEURON
  target code: TN-33376
alignment:
  target name: Descriptive statistics
  target url: https://talentneuron.com/
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/r-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all eight modules of the course, including all exercises, which require learners to demonstrate the ability to: - Install and operate R and RStudio - Import, organize, and tidy ecological datasets - Apply R functions to perform descriptive statistics and data transformations - Join and analyze relational datasets - Create and present ecological data visually using _ggplot2_ - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/7GW3PsBUSAmwPGmMOyquSA
name: R Boot Camp for Ecologists & Wildlife Biologists - STANDARD
image:
  id: https://badges.parchment.com/public/badges/7GW3PsBUSAmwPGmMOyquSA/image
image alt text: R Boot Camp for Ecologists & Wildlife Biologists - STANDARD badge image
achievement type: Course
description: This badge recognizes the successful completion of the R Boot Camp for Ecologists & Wildlife Biologists. Earners have gained foundational skills in R and RStudio, with a focus on ecological and wildlife-related applications. Skills include importing, cleaning, and transforming ecological datasets, managing relational data, and producing publication-quality data visualizations using ggplot2.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Rstudio
  target url: https://talentneuron.com/
  target description: RStudio is a tailored IDE for R programming, focusing on statistical analysis and data visualization.
  target framework: TALENT_NEURON
  target code: TN-34659
alignment:
  target name: R Programming Language
  target url: https://talentneuron.com/
  target description: R Programming Language is an open-source platform for statistical computing and graphics, enabling data manipulation, calculation, and graphical display.
  target framework: TALENT_NEURON
  target code: TN-33897
alignment:
  target name: Data cleaning
  target url: https://talentneuron.com/
  target description: Data cleaning refers to the process of detecting and correcting errors, inconsistencies, and inaccuracies in datasets to enhance data quality and reliability for analysis.
  target framework: TALENT_NEURON
  target code: TN-33376
alignment:
  target name: Descriptive statistics
  target url: https://talentneuron.com/
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/r-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all eight modules of the course, including all exercises, which require learners to demonstrate the ability to: - Install and operate R and RStudio - Import, organize, and tidy ecological datasets - Apply R functions to perform descriptive statistics and data transformations - Join and analyze relational datasets - Create and present ecological data visually using _ggplot2_ - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/gJmYATWjSPGrMOeaWtrUJw
name: Introduction to Ecological Statistics and Modeling - STANDARD
image:
  id: https://api.badgr.io/public/badges/gJmYATWjSPGrMOeaWtrUJw/image
description: This badge recognizes successful completion of Introduction to Ecological Statistics and Modeling. Earners gain essential quantitative skills in R to analyze, interpret, and present ecological data for research and publication. Coursework covers data wrangling and visualization, statistical inference for normal populations, nonparametric hypothesis testing, correlation, linear and multiple regression, ANOVA, and model selection. Badge earners can apply statistical reasoning to ecological datasets, interpret outputs, and select appropriate models for their research questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Descriptive statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/46677
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/ecomodel-r
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Import, tidy, and transform ecological datasets in R. - Visualize data clearly using R graphics libraries. - Apply the Central Limit Theorem to sampling distributions. - Calculate confidence intervals, p-values, and perform one- and two-sample t-tests. - Conduct and interpret nonparametric tests (permutation tests, hypothesis testing). - Measure correlation and carry out simple linear regression. - Perform multiple regression with continuous and categorical predictors. - Run ANOVA and interpret results in ecological contexts. - Diagnose multicollinearity, compare competing models, and combine information from multiple models. - Submit exercises demonstrating correct application of statistical analyses to ecological datasets. ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/skb9J53dTPGKu9p5QM17tA
name: Introduction to Ecological Statistics and Modeling - BASIC
image:
  id: https://api.badgr.io/public/badges/skb9J53dTPGKu9p5QM17tA/image
description: This badge recognizes successful completion of Introduction to Ecological Statistics and Modeling. Earners gain essential quantitative skills in R to analyze, interpret, and present ecological data for research and publication. Coursework covers data wrangling and visualization, statistical inference for normal populations, nonparametric hypothesis testing, correlation, linear and multiple regression, ANOVA, and model selection. Badge earners can apply statistical reasoning to ecological datasets, interpret outputs, and select appropriate models for their research questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Descriptive statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/46677
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/ecomodel-r
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Import, tidy, and transform ecological datasets in R. - Visualize data clearly using R graphics libraries. - Apply the Central Limit Theorem to sampling distributions. - Calculate confidence intervals, p-values, and perform one- and two-sample t-tests. - Conduct and interpret nonparametric tests (permutation tests, hypothesis testing). - Measure correlation and carry out simple linear regression. - Perform multiple regression with continuous and categorical predictors. - Run ANOVA and interpret results in ecological contexts. - Diagnose multicollinearity, compare competing models, and combine information from multiple models. - Submit exercises demonstrating correct application of statistical analyses to ecological datasets. ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/1aiWco9nSkqhGV_WB_YZfg
name: Research Design - BASIC
image:
  id: https://api.badgr.io/public/badges/1aiWco9nSkqhGV_WB_YZfg/image
description: This badge recognizes successful completion of the Research Design course. Earners can plan rigorous ecological and wildlife research studies by selecting and applying appropriate sampling techniques (systematic, random, stratified, multi-stage, mark-recapture, distance sampling) and experimental design methods (randomization, replication, blocking, BACI, factorial treatments, covariates). They are able to evaluate validity, minimize bias, and perform power and precision analyses in R to determine appropriate sample sizes and study feasibility.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Experimental design
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/19508
  target description: Experimental design refers to the planning and organization of scientific tests to examine hypotheses, ensuring credible and consistent outcomes through controlled, randomized, and repeatable methods.
  target framework: TALENT_NEURON
  target code: TN-19508
alignment:
  target name: Observational studies
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47206
  target description: Observational studies involve gathering data by monitoring subjects in their natural or controlled environments without interfering with the setting or participants.
  target framework: TALENT_NEURON
  target code: TN-47206
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/research-design
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Define research objectives and assess spatial, temporal, and sampling variability. - Apply appropriate sampling strategies (systematic, random, stratified, multi-stage, mark-recapture, distance sampling). - Identify and minimize sources of bias, error, and pseudo-replication. - Design experiments incorporating randomization, replication, blocking, BACI designs, factorial treatments, and covariates. - Evaluate internal and external validity in ecological study designs. - Perform power and precision analyses in R to calculate required sample sizes and assess study feasibility. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/Laa9Q3_nTke-NSmwa1FhIA
name: Research Design - STANDARD
image:
  id: https://api.badgr.io/public/badges/Laa9Q3_nTke-NSmwa1FhIA/image
description: This badge recognizes successful completion of the Research Design course. Earners can plan rigorous ecological and wildlife research studies by selecting and applying appropriate sampling techniques (systematic, random, stratified, multi-stage, mark-recapture, distance sampling) and experimental design methods (randomization, replication, blocking, BACI, factorial treatments, covariates). They are able to evaluate validity, minimize bias, and perform power and precision analyses in R to determine appropriate sample sizes and study feasibility.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Experimental design
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/19508
  target description: Experimental design refers to the planning and organization of scientific tests to examine hypotheses, ensuring credible and consistent outcomes through controlled, randomized, and repeatable methods.
  target framework: TALENT_NEURON
  target code: TN-19508
alignment:
  target name: Observational studies
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47206
  target description: Observational studies involve gathering data by monitoring subjects in their natural or controlled environments without interfering with the setting or participants.
  target framework: TALENT_NEURON
  target code: TN-47206
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/research-design
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Define research objectives and assess spatial, temporal, and sampling variability. - Apply appropriate sampling strategies (systematic, random, stratified, multi-stage, mark-recapture, distance sampling). - Identify and minimize sources of bias, error, and pseudo-replication. - Design experiments incorporating randomization, replication, blocking, BACI designs, factorial treatments, and covariates. - Evaluate internal and external validity in ecological study designs. - Perform power and precision analyses in R to calculate required sample sizes and assess study feasibility. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/-aseNeh9TtmhpJROVU5CAA
name: Generalized Linear, Additive, & Mixed Models - BASIC
image:
  id: https://api.badgr.io/public/badges/-aseNeh9TtmhpJROVU5CAA/image
achievement type: Course
description: This badge recognizes successful completion of Generalized Linear, Additive, & Mixed Models. Earners gain skills to analyze ecological data in R, including counts, proportions, and continuous measurements. They learn to fit and interpret generalized linear models (GLMs), extend them to address overdispersion and zero-inflation, and apply generalized additive models (GAMs) for flexible, non-linear relationships. The course also covers repeated measurements, profile analysis, and the use of fixed vs. random effects in mixed models. Learners practice residual diagnostics, model-checking, and model comparison/averaging using AIC, enabling them to build robust statistical models for ecological and wildlife applications.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/generalized-linear-models
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify and apply appropriate GLMs (Poisson, binomial, extensions) for ecological data. - Address overdispersion and zero-inflation in model fitting. - Fit generalized additive models (GAMs) to capture non-linear ecological relationships. - Perform model-checking and residual diagnostics in R. - Compare and average models using AIC. - Analyze repeated measurements data and conduct profile analysis. - Distinguish between fixed and random effects and fit mixed models accordingly. - Submit exercises demonstrating application of GLMs, GAMs, or mixed models to ecological datasets. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/lAQBY0WtQMaOj73RLiJOWQ
name: Generalized Linear, Additive, & Mixed Models - STANDARD
image:
  id: https://api.badgr.io/public/badges/lAQBY0WtQMaOj73RLiJOWQ/image
achievement type: Course
description: This badge recognizes successful completion of Generalized Linear, Additive, & Mixed Models. Earners gain skills to analyze ecological data in R, including counts, proportions, and continuous measurements. They learn to fit and interpret generalized linear models (GLMs), extend them to address overdispersion and zero-inflation, and apply generalized additive models (GAMs) for flexible, non-linear relationships. The course also covers repeated measurements, profile analysis, and the use of fixed vs. random effects in mixed models. Learners practice residual diagnostics, model-checking, and model comparison/averaging using AIC, enabling them to build robust statistical models for ecological and wildlife applications.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/generalized-linear-models
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify and apply appropriate GLMs (Poisson, binomial, extensions) for ecological data. - Address overdispersion and zero-inflation in model fitting. - Fit generalized additive models (GAMs) to capture non-linear ecological relationships. - Perform model-checking and residual diagnostics in R. - Compare and average models using AIC. - Analyze repeated measurements data and conduct profile analysis. - Distinguish between fixed and random effects and fit mixed models accordingly. - Submit exercises demonstrating application of GLMs, GAMs, or mixed models to ecological datasets. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/rj3dkWxgSgqUgsb28-MIvQ
name: Introduction to Bayesian Modeling in Ecology - BASIC
image:
  id: https://api.badgr.io/public/badges/rj3dkWxgSgqUgsb28-MIvQ/image
achievement type: Course
description: This badge recognizes successful completion of Introduction to Bayesian Modeling in Ecology. Earners develop foundational knowledge of Bayesian statistics and their application in ecology and wildlife management. Skills include specifying prior and likelihood distributions, applying Bayes’ Rule, and fitting normal, generalized linear, and hierarchical Bayesian models in R using the rjags package. Learners also gain experience with Markov chain Monte Carlo (MCMC) methods, model checking, model comparison, and effectively presenting Bayesian results.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Bayesian analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/35947
  target description: Bayesian analysis is a statistical method based on Bayes' theorem that updates the likelihood of a hypothesis when new data or evidence is introduced.
  target framework: TALENT_NEURON
  target code: TN-35947
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-statistics
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain the advantages and disadvantages of the Bayesian approach. - Specify prior and likelihood distributions and apply Bayes’ Rule to obtain posterior distributions. - Implement Bayesian models in R using the _rjags_ package. - Fit Bayesian normal, generalized linear, and hierarchical models. - Apply Markov chain Monte Carlo (MCMC) methods for model estimation. - Conduct Bayesian model checking and comparison. - Clearly interpret and communicate results from Bayesian analyses. - Submit assignments demonstrating correct implementation and interpretation of Bayesian models in R. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/jLZV8WOZQCu8iDTU_THnVA
name: Introduction to Bayesian Modeling in Ecology - STANDARD
image:
  id: https://api.badgr.io/public/badges/jLZV8WOZQCu8iDTU_THnVA/image
achievement type: Course
description: This badge recognizes successful completion of Introduction to Bayesian Modeling in Ecology. Earners develop foundational knowledge of Bayesian statistics and their application in ecology and wildlife management. Skills include specifying prior and likelihood distributions, applying Bayes’ Rule, and fitting normal, generalized linear, and hierarchical Bayesian models in R using the rjags package. Learners also gain experience with Markov chain Monte Carlo (MCMC) methods, model checking, model comparison, and effectively presenting Bayesian results.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Bayesian analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/35947
  target description: Bayesian analysis is a statistical method based on Bayes' theorem that updates the likelihood of a hypothesis when new data or evidence is introduced.
  target framework: TALENT_NEURON
  target code: TN-35947
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-statistics
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain the advantages and disadvantages of the Bayesian approach. - Specify prior and likelihood distributions and apply Bayes’ Rule to obtain posterior distributions. - Implement Bayesian models in R using the _rjags_ package. - Fit Bayesian normal, generalized linear, and hierarchical models. - Apply Markov chain Monte Carlo (MCMC) methods for model estimation. - Conduct Bayesian model checking and comparison. - Clearly interpret and communicate results from Bayesian analyses. - Submit assignments demonstrating correct implementation and interpretation of Bayesian models in R. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/-TFlWYdkSeawhvVFK178qw
name: Bayesian Hierarchical Modeling - STANDARD
image:
  id: https://api.badgr.io/public/badges/-TFlWYdkSeawhvVFK178qw/image
description: This badge recognizes the successful completion of Bayesian Hierarchical Modeling for Ecologists and Wildlife Biologists. Earners have developed applied skills in fitting, evaluating, and comparing ecological models using a Bayesian hierarchical framework. Skills include distinguishing between observation and ecological processes, fitting spatio-temporal models in R, accounting for spatial and temporal autocorrelation, checking model fit, and assessing predictive performance.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Bayesian analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/35947
  target description: Bayesian analysis is a statistical method based on Bayes' theorem that updates the likelihood of a hypothesis when new data or evidence is introduced.
  target framework: TALENT_NEURON
  target code: TN-35947
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-hierarchical-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Separate observation-process and ecological-process components within a hierarchical model - Identify appropriate observation-process models for various ecological datasets - Fit and interpret spatio-temporal models in R - Evaluate model fit and account for spatial and/or temporal autocorrelation - Compare and interpret competing model structures and predictive ability - Earn a C- (70%) or better on the final assessment - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/xzAbeUNFSqikzCUnFHgxbA
name: Bayesian Hierarchical Modeling - BASIC
image:
  id: https://api.badgr.io/public/badges/xzAbeUNFSqikzCUnFHgxbA/image
description: This badge recognizes the successful completion of Bayesian Hierarchical Modeling for Ecologists and Wildlife Biologists. Earners have developed applied skills in fitting, evaluating, and comparing ecological models using a Bayesian hierarchical framework. Skills include distinguishing between observation and ecological processes, fitting spatio-temporal models in R, accounting for spatial and temporal autocorrelation, checking model fit, and assessing predictive performance.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Bayesian analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/35947
  target description: Bayesian analysis is a statistical method based on Bayes' theorem that updates the likelihood of a hypothesis when new data or evidence is introduced.
  target framework: TALENT_NEURON
  target code: TN-35947
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-hierarchical-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Separate observation-process and ecological-process components within a hierarchical model - Identify appropriate observation-process models for various ecological datasets - Fit and interpret spatio-temporal models in R - Evaluate model fit and account for spatial and/or temporal autocorrelation - Compare and interpret competing model structures and predictive ability - Earn a C- (70%) or better on the final assessment - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/JUIyQa3oSouoxNUL4gu9dw
name: Python Boot Camp for Ecologists & Wildlife Biologists - BASIC
image:
  id: https://api.badgr.io/public/badges/JUIyQa3oSouoxNUL4gu9dw/image
description: This badge recognizes successful completion of the Python Boot Camp for Ecologists & Wildlife Biologists. Earners develop foundational coding skills in Python, with applications to data wrangling, visualization, and introductory machine learning. Coursework covers Python installation, programming fundamentals, Jupyter notebooks, the Pandas library for data manipulation, and scikit-learn for basic modeling. Badge earners can use Python interactively to import, clean, and analyze ecological datasets, create plots, and begin applying machine learning techniques.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Python
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18349
  target description: Python is a versatile, high-level language, prioritizing readability and ease, with extensive libraries, commonly utilized for web development, data analysis, AI, and scripting tasks.
  target framework: TALENT_NEURON
  target code: TN-18349
alignment:
  target name: Programming languages
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/44964
  target description: Programming languages are structured computer languages used to convey instructions to machines, primarily computers, for creating executable programs to perform various tasks and operations.
  target framework: TALENT_NEURON
  target code: TN-44964
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/python-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Install Python and supporting tools (Conda, Jupyter, IDEs). - Write and execute Python code interactively. - Assign variables, manipulate data types, and use functions. - Apply coding fundamentals, including conditionals, loops, and custom functions. - Ingest and manipulate data using Pandas dataframes. - Perform basic data wrangling (reshaping, subsetting, modifying values). - Create visualizations (scatter plots, histograms, basic charts). - Apply introductory machine learning models with scikit-learn. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/nHK32Mo4Q7yP4qtpuLSsyw
name: Python Boot Camp for Ecologists & Wildlife Biologists - STANDARD
image:
  id: https://api.badgr.io/public/badges/nHK32Mo4Q7yP4qtpuLSsyw/image
description: This badge recognizes successful completion of the Python Boot Camp for Ecologists & Wildlife Biologists. Earners develop foundational coding skills in Python, with applications to data wrangling, visualization, and introductory machine learning. Coursework covers Python installation, programming fundamentals, Jupyter notebooks, the Pandas library for data manipulation, and scikit-learn for basic modeling. Badge earners can use Python interactively to import, clean, and analyze ecological datasets, create plots, and begin applying machine learning techniques.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Python
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18349
  target description: Python is a versatile, high-level language, prioritizing readability and ease, with extensive libraries, commonly utilized for web development, data analysis, AI, and scripting tasks.
  target framework: TALENT_NEURON
  target code: TN-18349
alignment:
  target name: Programming languages
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/44964
  target description: Programming languages are structured computer languages used to convey instructions to machines, primarily computers, for creating executable programs to perform various tasks and operations.
  target framework: TALENT_NEURON
  target code: TN-44964
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/python-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Install Python and supporting tools (Conda, Jupyter, IDEs). - Write and execute Python code interactively. - Assign variables, manipulate data types, and use functions. - Apply coding fundamentals, including conditionals, loops, and custom functions. - Ingest and manipulate data using Pandas dataframes. - Perform basic data wrangling (reshaping, subsetting, modifying values). - Create visualizations (scatter plots, histograms, basic charts). - Apply introductory machine learning models with scikit-learn. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/HQ4rf6aARQiYrauLBkEZVA
name: Multivariate Ecological Community Analysis II - BASIC
image:
  id: https://api.badgr.io/public/badges/HQ4rf6aARQiYrauLBkEZVA/image
image alt text: Multivariate Ecological Community Analysis II - BASIC badge image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis II. Earners expand their skills beyond MECA I to apply advanced ordination, classification, group-testing, association, and trait-analysis tools to ecological datasets. Techniques covered include PCA, PCoA, NMS, clustering, MRPP, PerMANOVA, SumF, Indicator Species Analysis (ISA), Mantel Test, Compare Scores, and trait-based analyses such as Functional Diversity and Fourth Corner Analysis. Learners also gain experience in advanced graphing for ordination diagrams, interpreting dendrograms, and applying bootstrapping methods to multivariate analyses.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://talentneuron.com/
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Multivariate analysis
  target url: https://talentneuron.com/
  target description: Multivariate analysis is a statistical method that examines the connections between numerous variables and their combined effect on the results being investigated.
  target framework: TALENT_NEURON
  target code: TN-47175
alignment:
  target name: Multivariate statistics
  target url: https://talentneuron.com/
  target description: Multivariate statistics are techniques for analyzing data with multiple variables, revealing patterns and relationships beyond what univariate or bivariate analysis can detect.
  target framework: TALENT_NEURON
  target code: TN-39779
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/meca-ii
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, assignments, and required surveys. - Demonstrate the ability to: - Choose and apply advanced ordination methods (PCA, PCoA, NMS, NMS Scores). - Perform agglomerative clustering and select optimal clustering levels. - Apply group-testing procedures (MRPP, blocked MRPP, PerMANOVA, SumF, ISA). - Conduct association assessments (Mantel Test, Compare Scores). - Implement trait-based analyses (Functional Diversity, Fourth Corner Analysis). - Evaluate strengths, weaknesses, and assumptions of multivariate methods. - Interpret analysis outputs and communicate results using advanced graphing tools. - Apply bootstrapping techniques to multivariate analyses (e.g., PerMANOVA). - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/lJvCkgUxR-W36IiVHLexuw
name: Multivariate Ecological Community Analysis II - STANDARD
image:
  id: https://api.badgr.io/public/badges/lJvCkgUxR-W36IiVHLexuw/image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis II. Earners expand their skills beyond MECA I to apply advanced ordination, classification, group-testing, association, and trait-analysis tools to ecological datasets. Techniques covered include PCA, PCoA, NMS, clustering, MRPP, PerMANOVA, SumF, Indicator Species Analysis (ISA), Mantel Test, Compare Scores, and trait-based analyses such as Functional Diversity and Fourth Corner Analysis. Learners also gain experience in advanced graphing for ordination diagrams, interpreting dendrograms, and applying bootstrapping methods to multivariate analyses.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Multivariate analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47175
  target description: Multivariate analysis is a statistical method that examines the connections between numerous variables and their combined effect on the results being investigated.
  target framework: TALENT_NEURON
  target code: TN-47175
alignment:
  target name: Multivariate statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/39779
  target description: Multivariate statistics are techniques for analyzing data with multiple variables, revealing patterns and relationships beyond what univariate or bivariate analysis can detect.
  target framework: TALENT_NEURON
  target code: TN-39779
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/meca-ii
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, assignments, and required surveys. - Demonstrate the ability to: - Choose and apply advanced ordination methods (PCA, PCoA, NMS, NMS Scores). - Perform agglomerative clustering and select optimal clustering levels. - Apply group-testing procedures (MRPP, blocked MRPP, PerMANOVA, SumF, ISA). - Conduct association assessments (Mantel Test, Compare Scores). - Implement trait-based analyses (Functional Diversity, Fourth Corner Analysis). - Evaluate strengths, weaknesses, and assumptions of multivariate methods. - Interpret analysis outputs and communicate results using advanced graphing tools. - Apply bootstrapping techniques to multivariate analyses (e.g., PerMANOVA). - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/6wcYzly7SReJS8Ht3lgogA
name: Multivariate Ecological Community Analysis I - BASIC
image:
  id: https://api.badgr.io/public/badges/6wcYzly7SReJS8Ht3lgogA/image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis I. Earners can distinguish univariate from multivariate analyses, prepare ecological datasets for multivariate analysis, and select appropriate distance measures based on ecological and statistical properties. Learners gain proficiency in five guided ordination techniques—weighted averaging (WA), polar ordination (PO), canonical correspondence analysis (CCA), redundancy analysis (RDA), and fuzzy set ordination (FSO)—and learn how to interpret ordination diagrams. Coursework includes hands-on analysis using PC-ORD software, with optional exercises in R.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Multivariate analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47175
  target description: Multivariate analysis is a statistical method that examines the connections between numerous variables and their combined effect on the results being investigated.
  target framework: TALENT_NEURON
  target code: TN-47175
alignment:
  target name: Multivariate statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/39779
  target description: Multivariate statistics are techniques for analyzing data with multiple variables, revealing patterns and relationships beyond what univariate or bivariate analysis can detect.
  target framework: TALENT_NEURON
  target code: TN-39779
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/meca-i
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, assignments, and required surveys. - Demonstrate the ability to: - Distinguish between univariate and multivariate analyses. - Match dataset properties to appropriate distance measures. - Organize ecological data into matrices suitable for multivariate analysis. - Recognize when and how to modify data prior to analysis. - Set up and conduct analyses using WA, PO, CCA, RDA, and FSO. - Interpret analysis outputs and present ordination diagrams. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/QWmFhU-_TlqoPmzwwCzyDA
name: Multivariate Ecological Community Analysis I - STANDARD
image:
  id: https://api.badgr.io/public/badges/QWmFhU-_TlqoPmzwwCzyDA/image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis I. Earners can distinguish univariate from multivariate analyses, prepare ecological datasets for multivariate analysis, and select appropriate distance measures based on ecological and statistical properties. Learners gain proficiency in five guided ordination techniques—weighted averaging (WA), polar ordination (PO), canonical correspondence analysis (CCA), redundancy analysis (RDA), and fuzzy set ordination (FSO)—and learn how to interpret ordination diagrams. Coursework includes hands-on analysis using PC-ORD software, with optional exercises in R.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Multivariate analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/47175
  target description: Multivariate analysis is a statistical method that examines the connections between numerous variables and their combined effect on the results being investigated.
  target framework: TALENT_NEURON
  target code: TN-47175
alignment:
  target name: Multivariate statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/39779
  target description: Multivariate statistics are techniques for analyzing data with multiple variables, revealing patterns and relationships beyond what univariate or bivariate analysis can detect.
  target framework: TALENT_NEURON
  target code: TN-39779
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/meca-i
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, assignments, and required surveys. - Demonstrate the ability to: - Distinguish between univariate and multivariate analyses. - Match dataset properties to appropriate distance measures. - Organize ecological data into matrices suitable for multivariate analysis. - Recognize when and how to modify data prior to analysis. - Set up and conduct analyses using WA, PO, CCA, RDA, and FSO. - Interpret analysis outputs and present ordination diagrams. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/tWaBnUyfRfiur9ehm9CbKQ
name: Model Averaging - BASIC
image:
  id: https://api.badgr.io/public/badges/tWaBnUyfRfiur9ehm9CbKQ/image
description: This badge recognizes successful completion of Model Averaging in Ecology. Earners understand the importance of accounting for both parameter and model uncertainty in ecological data analysis. They gain practical skills in applying Bayesian and frequentist model averaging methods, evaluating when model averaging is appropriate, and interpreting results. Using R, learners conduct point and interval estimation, prediction-based averaging, and implement relevant R packages to produce defensible ecological inferences.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/model-averaging-ecology
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and required surveys. - Demonstrate the ability to: - Explain the need for model averaging and its role in addressing model uncertainty. - Evaluate when model averaging is useful and when it is not appropriate. - Apply Bayesian model averaging techniques, including classical and prediction-based approaches. - Implement frequentist model averaging for point and interval estimation. - Use relevant R packages to code and perform model averaging analyses. - Interpret and clearly describe results obtained from model averaging. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/RhyJHNQtQ72uPrteuFectg
name: Model Averaging - STANDARD
image:
  id: https://api.badgr.io/public/badges/RhyJHNQtQ72uPrteuFectg/image
description: This badge recognizes successful completion of Model Averaging in Ecology. Earners understand the importance of accounting for both parameter and model uncertainty in ecological data analysis. They gain practical skills in applying Bayesian and frequentist model averaging methods, evaluating when model averaging is appropriate, and interpreting results. Using R, learners conduct point and interval estimation, prediction-based averaging, and implement relevant R packages to produce defensible ecological inferences.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/model-averaging-ecology
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and required surveys. - Demonstrate the ability to: - Explain the need for model averaging and its role in addressing model uncertainty. - Evaluate when model averaging is useful and when it is not appropriate. - Apply Bayesian model averaging techniques, including classical and prediction-based approaches. - Implement frequentist model averaging for point and interval estimation. - Use relevant R packages to code and perform model averaging analyses. - Interpret and clearly describe results obtained from model averaging. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/vPaKHKYCTXi1v_ar15k5uA
name: Applied Project
image:
  id: https://api.badgr.io/public/badges/vPaKHKYCTXi1v_ar15k5uA/image
description: TBD
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  narrative: TBD
type: BadgeClass

id: https://api.badgr.io/public/badges/neFF2BXUT-SIJlGoGrxexQ
name: Introduction to Occupancy Modeling - BASIC
image:
  id: https://badges.parchment.com/public/badges/neFF2BXUT-SIJlGoGrxexQ/image
image alt text: Introduction to Occupancy Modeling - BASIC badge image
description: This badge recognizes successful completion of Introduction to Occupancy Modeling. Earners learn how to account for imperfect detection when analyzing species presence/absence data, improving the accuracy of ecological inference. Coursework covers single-season occupancy models, incorporating covariates, dealing with missing data, model assumptions, and study design. Learners practice applying Program PRESENCE and RPresence to estimate occupancy and assess model fit while considering sampling unit definition, survey effort allocation, and spatial correlation. Badge earners can design and implement studies of species occurrence that properly account for detection probability.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://talentneuron.com/
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/occupancy-modeling-intro
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including applied analyses in Program PRESENCE and RPresence. - Demonstrate the ability to: - Explain why accounting for imperfect detection is essential in species occurrence studies. - Apply probability-based methods for estimating occupancy. - Implement single-season occupancy models, with and without covariates. - Handle missing observations and unequal effort in occupancy data. - Assess model assumptions and evaluate model fit. - Estimate occupancy for small areas and finite populations, considering spatial correlation. - Define sampling units, repeat surveys, and allocate effort effectively in study design. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/zvHk_StvTmq9f99mR8UrLg
name: Introduction to Occupancy Modeling - STANDARD
image:
  id: https://badges.parchment.com/public/badges/zvHk_StvTmq9f99mR8UrLg/image
description: This badge recognizes successful completion of Introduction to Occupancy Modeling. Earners learn how to account for imperfect detection when analyzing species presence/absence data, improving the accuracy of ecological inference. Coursework covers single-season occupancy models, incorporating covariates, dealing with missing data, model assumptions, and study design. Learners practice applying Program PRESENCE and RPresence to estimate occupancy and assess model fit while considering sampling unit definition, survey effort allocation, and spatial correlation. Badge earners can design and implement studies of species occurrence that properly account for detection probability.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/occupancy-modeling-intro
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including applied analyses in Program PRESENCE and RPresence. - Demonstrate the ability to: - Explain why accounting for imperfect detection is essential in species occurrence studies. - Apply probability-based methods for estimating occupancy. - Implement single-season occupancy models, with and without covariates. - Handle missing observations and unequal effort in occupancy data. - Assess model assumptions and evaluate model fit. - Estimate occupancy for small areas and finite populations, considering spatial correlation. - Define sampling units, repeat surveys, and allocate effort effectively in study design. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/lDWFprZ6Qrm1XuWk6BWSLA
name: Advanced Occupancy Modeling - BASIC
image:
  id: https://badges.parchment.com/public/badges/lDWFprZ6Qrm1XuWk6BWSLA/image
description: This badge recognizes successful completion of Advanced Occupancy Modeling. Earners expand their knowledge of species occurrence modeling by learning multi-scale, multi-state, species co-occurrence, and community-level occupancy approaches. Skills include accounting for correlated detection, false positives, and spatial correlation; implementing dynamic and joint occupancy-habitat dynamics models; and presenting results through plots and species distribution maps in R. Badge earners can design and analyze advanced occupancy studies that provide robust insights into species distributions and community dynamics.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/occupancymodeling-ii
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including advanced analyses in R. - Demonstrate the ability to: - Review and extend static occupancy models with covariates and species distribution mapping. - Apply correlated detection and multi-scale occupancy models. - Account for spatial correlation in occupancy data. - Implement static and dynamic multi-state occupancy models. - Address false positive detections in occupancy studies. - Conduct species co-occurrence and community-level occupancy modeling. - Apply joint occupancy-habitat dynamics models. - Present results using R, including plotting and mapping outputs. - Submit assignments or projects demonstrating correct application and interpretation of advanced occupancy models in ecological research. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/VVEn1aOZT6WDxRJ08eykkA
name: Advanced Occupancy Modeling - STANDARD
image:
  id: https://badges.parchment.com/public/badges/VVEn1aOZT6WDxRJ08eykkA/image
description: This badge recognizes successful completion of Advanced Occupancy Modeling. Earners expand their knowledge of species occurrence modeling by learning multi-scale, multi-state, species co-occurrence, and community-level occupancy approaches. Skills include accounting for correlated detection, false positives, and spatial correlation; implementing dynamic and joint occupancy-habitat dynamics models; and presenting results through plots and species distribution maps in R. Badge earners can design and analyze advanced occupancy studies that provide robust insights into species distributions and community dynamics.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/occupancymodeling-ii
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including advanced analyses in R. - Demonstrate the ability to: - Review and extend static occupancy models with covariates and species distribution mapping. - Apply correlated detection and multi-scale occupancy models. - Account for spatial correlation in occupancy data. - Implement static and dynamic multi-state occupancy models. - Address false positive detections in occupancy studies. - Conduct species co-occurrence and community-level occupancy modeling. - Apply joint occupancy-habitat dynamics models. - Present results using R, including plotting and mapping outputs. - Submit assignments or projects demonstrating correct application and interpretation of advanced occupancy models in ecological research. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/4RpNvEw7QlSZc7b34QVICw
name: Introduction to Capture-Mark-Recapture - BASIC
image:
  id: https://badges.parchment.com/public/badges/4RpNvEw7QlSZc7b34QVICw/image
image alt text: Introduction to Capture-Mark-Recapture - BASIC badge image
description: This badge recognizes successful completion of Introduction to Capture-Mark-Recapture. Earners gain a foundation in capture-mark-recapture (CMR) techniques for estimating abundance, density, growth rates, and vital rates in wildlife populations. Skills include linking research questions to study design, applying appropriate sampling methods informed by animal behavior, and analyzing data using MARK and RMark. Learners understand model assumptions, limits, and selection theory, and practice using simulations to improve study design. A case study on grizzly bear population research provides hands-on application of concepts to real-world ecological management questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://talentneuron.com/
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/capture-mark-recapture
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, exercises, and required surveys. - Demonstrate the ability to: - Frame ecological research questions and hypotheses for CMR studies. - Define study populations and identify objectives aligned with population monitoring. - Apply foundations of CMR modeling to detection and non-detection data. - Differentiate among open vs. closed population models, spatial (SECR) vs. non-spatial, and mark-resight approaches. - Incorporate covariates appropriately and recognize their limits. - Link animal behavior, life history, and sampling design to analytical approaches. - Use model selection theory to evaluate assumptions and limitations. - Estimate abundance, density, and growth rates from CMR data. - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/OqtfkNBLQ0uC-QVaZMTAbw
name: Introduction to Capture-Mark-Recapture - STANDARD
image:
  id: https://badges.parchment.com/public/badges/OqtfkNBLQ0uC-QVaZMTAbw/image
image alt text: Introduction to Capture-Mark-Recapture - STANDARD badge image
description: This badge recognizes successful completion of Introduction to Capture-Mark-Recapture. Earners gain a foundation in capture-mark-recapture (CMR) techniques for estimating abundance, density, growth rates, and vital rates in wildlife populations. Skills include linking research questions to study design, applying appropriate sampling methods informed by animal behavior, and analyzing data using MARK and RMark. Learners understand model assumptions, limits, and selection theory, and practice using simulations to improve study design. A case study on grizzly bear population research provides hands-on application of concepts to real-world ecological management questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://talentneuron.com/
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/capture-mark-recapture
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including quizzes, exercises, and required surveys. - Demonstrate the ability to: - Frame ecological research questions and hypotheses for CMR studies. - Define study populations and identify objectives aligned with population monitoring. - Apply foundations of CMR modeling to detection and non-detection data. - Differentiate among open vs. closed population models, spatial (SECR) vs. non-spatial, and mark-resight approaches. - Incorporate covariates appropriately and recognize their limits. - Link animal behavior, life history, and sampling design to analytical approaches. - Use model selection theory to evaluate assumptions and limitations. - Estimate abundance, density, and growth rates from CMR data. - Earn a C- (70%) or better on the final exam - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/pBSjWIvJQvWj1q7JtUigJw
name: Bayesian Causal Networks for Complex Multivariate Systems - BASIC
image:
  id: https://badges.parchment.com/public/badges/pBSjWIvJQvWj1q7JtUigJw/image
description: This badge recognizes successful completion of Bayesian Causal Networks for Complex Multivariate Systems. Earners develop proficiency in creating, calibrating, and updating Bayesian Causal Network (BCN) models to represent causal relationships in complex ecological systems. Skills include using Netica software to build influence diagrams, decision nets, and Bayesian networks; performing sensitivity analysis; and applying scenario testing to predict system responses. Badge earners can design and refine BCN models to identify leverage points for intervention and support strategic ecological decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Causal Inference
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/58601
  target description: Causal Inference refers to the method of identifying and verifying cause-and-effect connections from observed data, employing statistical models to control for confounding factors and infer causality.
  target framework: TALENT_NEURON
  target code: TN-58601
alignment:
  target name: Causal Analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/63991
  target description: Causal Analysis identifies and evaluates underlying reasons for outcomes, enabling informed decision-making and effective problem-solving strategies.
  target framework: TALENT_NEURON
  target code: TN-63991
alignment:
  target name: Machine learning
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/30919
  target description: Machine learning is a subset of AI concerned with developing systems that learn and enhance through experience, employing algorithms to analyze data, learn from it, and make decisions autonomously.
  target framework: TALENT_NEURON
  target code: TN-30919
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-causal-network-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain Bayesian Causal Network (BCN) concepts and their applications to complex multivariate systems. - Research and document frameworks for BCN modeling relevant to ecological problems. - Create influence diagrams and Decision Nets in Netica. - Build, calibrate, and simplify BCN models. - Conduct sensitivity analysis and scenario testing to assess system behavior. - Update BCN models with new data to refine predictions. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/WAv51ZdjRo6rQwIU3lfKDA
name: Bayesian Causal Networks for Complex Multivariate Systems - STANDARD
image:
  id: https://badges.parchment.com/public/badges/WAv51ZdjRo6rQwIU3lfKDA/image
description: This badge recognizes successful completion of Bayesian Causal Networks for Complex Multivariate Systems. Earners develop proficiency in creating, calibrating, and updating Bayesian Causal Network (BCN) models to represent causal relationships in complex ecological systems. Skills include using Netica software to build influence diagrams, decision nets, and Bayesian networks; performing sensitivity analysis; and applying scenario testing to predict system responses. Badge earners can design and refine BCN models to identify leverage points for intervention and support strategic ecological decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Causal Inference
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/58601
  target description: Causal Inference refers to the method of identifying and verifying cause-and-effect connections from observed data, employing statistical models to control for confounding factors and infer causality.
  target framework: TALENT_NEURON
  target code: TN-58601
alignment:
  target name: Causal Analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/63991
  target description: Causal Analysis identifies and evaluates underlying reasons for outcomes, enabling informed decision-making and effective problem-solving strategies.
  target framework: TALENT_NEURON
  target code: TN-63991
alignment:
  target name: Machine learning
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/30919
  target description: Machine learning is a subset of AI concerned with developing systems that learn and enhance through experience, employing algorithms to analyze data, learn from it, and make decisions autonomously.
  target framework: TALENT_NEURON
  target code: TN-30919
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-causal-network-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain Bayesian Causal Network (BCN) concepts and their applications to complex multivariate systems. - Research and document frameworks for BCN modeling relevant to ecological problems. - Create influence diagrams and Decision Nets in Netica. - Build, calibrate, and simplify BCN models. - Conduct sensitivity analysis and scenario testing to assess system behavior. - Update BCN models with new data to refine predictions. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/40pS8nnlQMCbgNgWyvbPxw
name: Distance Sampling - BASIC
image:
  id: https://badges.parchment.com/public/badges/40pS8nnlQMCbgNgWyvbPxw/image
description: This badge recognizes successful completion of Distance Sampling. Earners gain a foundation in designing and implementing distance sampling studies for estimating species abundance and distribution while accounting for imperfect detection. Learners practice unbiased sampling design, data collection, data management, and analysis using the R package unmarked. Skills include applying distance sampling methods with point counts and line transects for solitary and social species, incorporating covariates, and comparing and interpreting models. The course also introduces advanced extensions, including temporal replicates, seasonal data, and Bayesian approaches.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/distance-sampling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify ecological research questions and monitoring priorities for abundance estimation. - Design unbiased population sampling approaches for point counts and line transects. - Explain the importance of detection probability in abundance estimation. - Collect and manage distance sampling field data for analysis. - Implement distance sampling models in R using the *unmarked* package. - Apply distance sampling to solitary species (point counts, line transects) and social species (line transects). - Incorporate covariates on abundance and detection probability to test ecological hypotheses. - Compare models, assess fit, and interpret results. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/H4MBrmoHRg6MCbvgZI8R3Q
name: Distance Sampling - STANDARD
image:
  id: https://badges.parchment.com/public/badges/H4MBrmoHRg6MCbvgZI8R3Q/image
description: This badge recognizes successful completion of Distance Sampling. Earners gain a foundation in designing and implementing distance sampling studies for estimating species abundance and distribution while accounting for imperfect detection. Learners practice unbiased sampling design, data collection, data management, and analysis using the R package unmarked. Skills include applying distance sampling methods with point counts and line transects for solitary and social species, incorporating covariates, and comparing and interpreting models. The course also introduces advanced extensions, including temporal replicates, seasonal data, and Bayesian approaches.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/distance-sampling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify ecological research questions and monitoring priorities for abundance estimation. - Design unbiased population sampling approaches for point counts and line transects. - Explain the importance of detection probability in abundance estimation. - Collect and manage distance sampling field data for analysis. - Implement distance sampling models in R using the *unmarked* package. - Apply distance sampling to solitary species (point counts, line transects) and social species (line transects). - Incorporate covariates on abundance and detection probability to test ecological hypotheses. - Compare models, assess fit, and interpret results. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/ubaAF91qR8WLYE5xto_HOw
name: Species Distribution Modeling - BASIC
image:
  id: https://badges.parchment.com/public/badges/ubaAF91qR8WLYE5xto_HOw/image
description: This badge recognizes the successful completion of Species Distribution Modeling. Earners have developed applied skills to design, fit, evaluate, and interpret species distribution models (SDMs) and ecological niche models (ENMs) using R. Skills include preparing biodiversity and environmental datasets, selecting appropriate modeling frameworks, visualizing and assessing model performance, and applying SDMs to ecological and conservation questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/species-distribution-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Describe the theoretical foundations of species distribution and ecological niche modeling - Evaluate and select appropriate modeling frameworks for different ecological data types and goals - Compile and clean biodiversity and environmental data for SDM and ENM analyses - Fit, visualize, and assess SDMs using R packages and performance metrics - Compare and interpret models based on predictive accuracy and transferability - Apply SDM techniques to ecological and conservation case studies - Earn a C- (70%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final assessment earns 1 credit toward certification (Category F: Modeling and Quantitative Methods) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/2IHG_38ST2uGP_b_kWmM3g
name: Species Distribution Modeling - STANDARD
image:
  id: https://badges.parchment.com/public/badges/2IHG_38ST2uGP_b_kWmM3g/image
description: This badge recognizes the successful completion of Species Distribution Modeling. Earners have developed applied skills to design, fit, evaluate, and interpret species distribution models (SDMs) and ecological niche models (ENMs) using R. Skills include preparing biodiversity and environmental datasets, selecting appropriate modeling frameworks, visualizing and assessing model performance, and applying SDMs to ecological and conservation questions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data modeling
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/18420
  target description: Data modeling is the creation of simplified depictions of intricate data systems, enabling effective database development, storage, and precise data access for various organizational purposes.
  target framework: TALENT_NEURON
  target code: TN-18420
alignment:
  target name: Statistical analysis
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/17285
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/species-distribution-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Describe the theoretical foundations of species distribution and ecological niche modeling - Evaluate and select appropriate modeling frameworks for different ecological data types and goals - Compile and clean biodiversity and environmental data for SDM and ENM analyses - Fit, visualize, and assess SDMs using R packages and performance metrics - Compare and interpret models based on predictive accuracy and transferability - Apply SDM techniques to ecological and conservation case studies - Earn a C- (70%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final assessment earns 1 credit toward certification (Category F: Modeling and Quantitative Methods) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/Slep2lOCSwqhVanpfGM-zQ
name: Wildlife Capture and Chemical Immobilization (Online & Field)
image:
  id: https://badges.parchment.com/public/badges/Slep2lOCSwqhVanpfGM-zQ/image
image alt text: Wildlife Capture and Chemical Immobilization (Online & Field) badge image
description: This badge recognizes successful completion of Wildlife Capture and Chemical Immobilization. Learners develop foundational competencies in planning and executing wildlife capture and chemical immobilization activities while prioritizing animal welfare, human safety, and ethical research and management practices. Coursework covers capture equipment and delivery systems, pharmacology of immobilization drugs, dosage calculation, species-specific considerations, safety protocols, patient monitoring, biological sample collection, and post-capture care. Learners apply best practices for handling wildlife during capture operations and demonstrate the ability to support research, conservation, and animal care activities in field and applied settings.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/wcci-field-2024
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Select appropriate capture equipment and drug delivery systems for specific capture scenarios. - Determine appropriate immobilization drugs and calculate accurate dosages by species. - Apply safety protocols for drug handling, capture operations, and chemical immobilization. - Monitor immobilized animals and demonstrate proper patient care. - Collect biological tissue samples for research and disease monitoring. - Fit animals with radio collars or other tracking tags. - Administer vaccinations, antibiotics, and reversal agents as appropriate. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/JW11tNTRQyWJeOkkLhWObg
name: Introduction to Remote Sensing - BASIC
image:
  id: https://badges.parchment.com/public/badges/JW11tNTRQyWJeOkkLhWObg/image
image alt text: Introduction to Remote Sensing - BASIC badge image
description: This badge recognizes successful completion of Spatial Analysis & Remote Sensing for Natural Resources – BASIC. Learners develop foundational competencies in spatially explicit data analysis using remote sensing techniques to support forest monitoring, wildlife research, and natural resource management. Coursework introduces core remote sensing concepts, including satellite platforms and image characteristics, image acquisition and preprocessing, multispectral imagery, land cover classification, and accuracy assessment. Learners apply practical techniques in image interpretation, vegetation indices, change detection, and visualization, while integrating raster and vector data using QGIS. By the end of the course, learners can interpret and analyze spatial data to inform ecological and natural resource decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/remote-sensing
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and required surveys. - Demonstrate the ability to: - Identify appropriate remote sensing platforms and image characteristics for ecological applications. - Acquire, preprocess, and manage satellite imagery for spatial analysis. - Interpret multispectral imagery and calculate vegetation indices. - Perform supervised land cover classification and assess classification accuracy. - Apply change detection techniques for forest and land cover monitoring. - Visualize and communicate spatial analysis results effectively. - Integrate raster and vector data within a GIS environment. ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/Vfpftg4ATiiqQhzdREyRDg
name: Introduction to Spatial Analysis in QGIS - BASIC
image:
  id: https://badges.parchment.com/public/badges/Vfpftg4ATiiqQhzdREyRDg/image
image alt text: R Boot Camp for Ecologists & Wildlife Biologists - BASIC badge image
achievement type: Course
description: This badge recognizes successful completion of Introduction to Spatial Analysis in QGIS – BASIC. Learners develop foundational competencies in applying Geographic Information Systems (GIS) to analyze and visualize spatial data in natural science, wildlife, and natural resource contexts. Coursework introduces core GIS concepts, including cartography, geodesy, coordinate reference systems, and map projections. Learners gain hands-on experience acquiring spatial data, preparing datasets, creating and editing vector data, working with raster datasets, performing spatial analyses, querying attribute tables, and designing maps. Using QGIS, learners apply practical workflows for spatial analysis, data management, and web-based map publishing to support research and decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data analysis
  target url: https://talentneuron.com/
  target framework: TALENT_NEURON
  target code: TN-17153
alignment:
  target name: QGIS
  target url: https://talentneuron.com/
  target framework: TALENT_NEURON
  target code: TN-37893
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/spatial-analysis
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all required course modules and tutorials. Demonstrate the ability to: - Navigate the QGIS interface and manage GIS projects. - Acquire and prepare spatial data from online repositories. - Apply coordinate reference systems and map projections correctly. - Create, edit, and digitize vector datasets (points and polygons). - Perform attribute queries and spatial analyses. - Work with raster datasets and extract spatial values. - Design professional-quality maps and publish maps online. - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/UsKgdYedTXOsCXnVGj3M5A
name: Introduction to Spatial Analysis in QGIS - STANDARD
image:
  id: https://badges.parchment.com/public/badges/UsKgdYedTXOsCXnVGj3M5A/image
image alt text: R Boot Camp for Ecologists & Wildlife Biologists - BASIC badge image
achievement type: Course
description: This badge recognizes successful completion of Introduction to Spatial Analysis in QGIS – STANDARD. Learners develop foundational competencies in applying Geographic Information Systems (GIS) to analyze and visualize spatial data in natural science, wildlife, and natural resource contexts. Coursework introduces core GIS concepts, including cartography, geodesy, coordinate reference systems, and map projections. Learners gain hands-on experience acquiring spatial data, preparing datasets, creating and editing vector data, working with raster datasets, performing spatial analyses, querying attribute tables, and designing maps. Using QGIS, learners apply practical workflows for spatial analysis, data management, and web-based map publishing to support research and decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data analysis
  target url: https://talentneuron.com/
  target description: Data analysis involves examining, cleaning, transforming, and modeling data to reveal valuable insights, inform decisions, and support conclusions.
  target framework: TALENT_NEURON
  target code: TN-17153
alignment:
  target name: QGIS
  target url: https://talentneuron.com/
  target description: QGIS is a free and open-source Geographic Information System utilized for mapping, spatial analysis, and the visualization of geospatial data in various sectors.
  target framework: TALENT_NEURON
  target code: TN-37893
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/spatial-analysis
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all required course modules and tutorials. Demonstrate the ability to: - Navigate the QGIS interface and manage GIS projects. - Acquire and prepare spatial data from online repositories. - Apply coordinate reference systems and map projections correctly. - Create, edit, and digitize vector datasets (points and polygons). - Perform attribute queries and spatial analyses. - Work with raster datasets and extract spatial values. - Design professional-quality maps and publish maps online. - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/exdCHO6VSOWjTca465YHNQ
name: Introduction to Spatial Analysis in QGIS - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/exdCHO6VSOWjTca465YHNQ/image
image alt text: R Boot Camp for Ecologists & Wildlife Biologists - BASIC badge image
achievement type: Course
description: This badge recognizes successful completion of Introduction to Spatial Analysis in QGIS – PREMIUM. Learners develop foundational competencies in applying Geographic Information Systems (GIS) to analyze and visualize spatial data in natural science, wildlife, and natural resource contexts. Coursework introduces core GIS concepts, including cartography, geodesy, coordinate reference systems, and map projections. Learners gain hands-on experience acquiring spatial data, preparing datasets, creating and editing vector data, working with raster datasets, performing spatial analyses, querying attribute tables, and designing maps. Using QGIS, learners apply practical workflows for spatial analysis, data management, and web-based map publishing to support research and decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Data analysis
  target url: https://talentneuron.com/
  target description: Data analysis involves examining, cleaning, transforming, and modeling data to reveal valuable insights, inform decisions, and support conclusions.
  target framework: TALENT_NEURON
  target code: TN-17153
alignment:
  target name: QGIS
  target url: https://talentneuron.com/
  target description: QGIS is a free and open-source Geographic Information System utilized for mapping, spatial analysis, and the visualization of geospatial data in various sectors.
  target framework: TALENT_NEURON
  target code: TN-37893
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/spatial-analysis
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all required course modules and tutorials. Demonstrate the ability to: - Navigate the QGIS interface and manage GIS projects. - Acquire and prepare spatial data from online repositories. - Apply coordinate reference systems and map projections correctly. - Create, edit, and digitize vector datasets (points and polygons). - Perform attribute queries and spatial analyses. - Work with raster datasets and extract spatial values. - Design professional-quality maps and publish maps online. - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/Ebi5DBIuSgCwb-H9PjcEjg
name: Conservation Standards - BASIC
image:
  id: https://badges.parchment.com/public/badges/Ebi5DBIuSgCwb-H9PjcEjg/image
image alt text: Conservation Standards - BASIC badge image
description: This course teaches the principles, tools, and best practices of the Conservation Standards framework to support effective, collaborative conservation planning that addresses ecological threats, integrates human well-being, and accounts for climate change. At the BASIC level, learners apply the Conservation Standards framework independently through self-paced exercises based on a real-world case study. Emphasis is placed on understanding core concepts, following structured workflows, and developing familiarity with conservation planning tools.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Systems thinking
  target url: https://talentneuron.com/
  target framework: TALENT_NEURON
  target code: TN-31174
alignment:
  target name: Conservation Planning
  target url: https://talentneuron.com/
  target framework: TALENT_NEURON
  target code: TN-55891
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/open-standards
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Lead or substantially contribute to team-based conservation planning processes. - Apply the Conservation Standards framework across all planning stages. - Facilitate consensus-building around scope, vision, and priorities. - Develop robust situation analyses and results chains. - Integrate human well-being and climate change considerations into strategic decisions. - Design comprehensive monitoring, evaluation, and adaptive management plans. - Translate planning outputs into actionable work plans. ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/kWHtvmNNQ3WM7F8C1TpMmw
name: Geospatial Modeling in QGIS and R - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/kWHtvmNNQ3WM7F8C1TpMmw/image
image alt text: Geospatial Modeling in QGIS and R - PREMIUM badge image
description: This badge recognizes successful completion of Geospatial Modeling with QGIS and R. Earners gain skills in processing and analyzing spatial data to study wildlife home range and habitat use. Learners use QGIS, R, and the Geospatial Modeling Environment (GME) to create and transform spatial data, generate shape files, and estimate home ranges. They apply raster land cover and remote sensing data to conduct vegetation analysis and compare used vs. available habitats. Badge earners can integrate spatial data layers, calculate geometry, and conduct habitat assessments to inform population and habitat management decisions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/geospatial-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including applied exercises in QGIS, R, and GME. - Demonstrate the ability to: - Download and prepare spatial datasets from online sources. - Create, manage, and transform vector data (points, shape files, coordinate systems). - Process raw point location data to calculate home ranges. - Use QGIS and GME to analyze and visualize home range data. - Apply raster data for vegetation and habitat analysis. - Distinguish between used and available habitats and conduct statistical comparisons. - Submit assignments or projects demonstrating home range and habitat analysis using QGIS and R. - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS • CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit • ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification • TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) • TWS Continuing Education: Course completion earns 16 CEUs • ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/GH6rkjFKRW2n14h8UWaYlg
name: Computer Vision for Ecologists - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/GH6rkjFKRW2n14h8UWaYlg/image
description: This badge recognizes successful completion of Computer Vision for Ecologists. Earners demonstrate applied skills in preparing ecological datasets, building computer vision workflows, and deploying machine learning models to analyze large-scale ecological data.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Statistical analysis
  target url: https://talentneuron.com/
  target description: Statistical analysis is the methodical study of data to uncover patterns and trends using software and mathematical approaches.
  target framework: TALENT_NEURON
  target code: TN-17285
criteria:
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the course, including all exercises, which require learners to demonstrate the ability to: - Apply best practices for ecological data handling and management. - Clean and prepare datasets using tools such as OpenRefine or R. - Configure Python environments and develop workflows using Jupyter notebooks. - Acquire and manage data from external sources, including web-based data. - Apply machine learning and introductory deep learning techniques to ecological datasets. - Develop and deploy a basic computer vision application for ecological analysis. - Earn a B- (80%) or higher on the final assessment - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/UIG-fRctR16-flCJM94Xrw
name: Biology and Ecology of Sharks and Their Relatives - BASIC
image:
  id: https://badges.parchment.com/public/badges/UIG-fRctR16-flCJM94Xrw/image
image alt text: Biology and Ecology of Sharks and Their Relatives - BASIC badge image
description: This badge recognizes the successful completion of Shark Biology, Ecology, and Conservation. Earners have gained a broad understanding of shark biology, evolution, ecology, and behavior, as well as the scientific tools and methods used to study sharks. Skills include interpreting shark life history strategies, ecological roles, and migratory behavior, and applying scientific reasoning to conservation and management challenges facing sharks worldwide.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/biology-and-ecology-of-sharks-and-their-relatives
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the online course, including all lectures, readings, and activities. - Demonstrate the ability to: - Identify major groups of sharks and explain their evolutionary history - Describe shark reproductive strategies and life history traits - Explain the ecological roles and behaviors of sharks - Interpret conservation and management issues related to shark migration, fisheries, and ecosystem function - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/-zeBFaRjQXCFSwqLTgn9yw
name: Integrated Population Models- BASIC
image:
  id: https://badges.parchment.com/public/badges/-zeBFaRjQXCFSwqLTgn9yw/image
achievement type: Course
description: This badge recognizes the successful completion of Integrated Population Models. Earners have gained applied skills in fitting and evaluating integrated population models (IPMs) using a Bayesian framework. Skills include combining multiple data sources, constructing population and observation models, fitting models in R using JAGS, and evaluating model fit and predictive performance through model checking and comparison.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/integrated-population-models
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Explain the structure and purpose of integrated population models (IPMs) - Construct population and observation models for multiple data types - Fit Bayesian IPMs in R using JAGS - Evaluate model assumptions and assess model fit - Compare competing Bayesian IPMs using WAIC weights - Estimate demographic parameters including survival, productivity, immigration, and dispersal - Incorporate random effects and state-space structures into IPMs - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/9r5r2pS9TISHGPqn4oJ8FA
name: Biology and Ecology of Sharks and Their Relatives - Online & Field
image:
  id: https://badges.parchment.com/public/badges/9r5r2pS9TISHGPqn4oJ8FA/image
image alt text: Biology and Ecology of Sharks and Their Relatives - Online & Field badge image
description: This badge recognizes the successful completion of Biology and Ecology of Sharks and Their Relatives (Online & Field). Earners have gained a broad understanding of shark biology, evolution, ecology, and behavior as well as the scientific tools and methods used to study sharks. Skills include interpreting shark life history strategies, ecological roles, and migratory behavior, and applying scientific reasoning to conservation and management challenges facing sharks worldwide.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/biology-and-ecology-of-sharks-and-their-relatives
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the online course, including all lectures, readings, and activities. - Actively participate in a 3-day field experience aboard a research vessel. - Demonstrate the ability to: - Identify major groups of sharks and explain their evolutionary history - Describe shark reproductive strategies and life history traits - Explain the ecological roles and behaviors of sharks - Interpret conservation and management issues related to shark migration, fisheries, and ecosystem function - Earn a C- (70%) or better on the final project ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Continuing Education: Course completion earns 16 CEUs - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final project earns 1 credit toward certification in Wildlife Management and Biology
type: BadgeClass

id: https://api.badgr.io/public/badges/-1rhrjVcTcauSteTEN01sg
name: Environmental Justice in Conservation: From Principles to Practice - STANDARD
image:
  id: https://badges.parchment.com/public/badges/-1rhrjVcTcauSteTEN01sg/image
image alt text: Environmental Justice in Conservation: From Principles to Practice - STANDARD badge image
achievement type: Course
description: This badge recognizes the successful completion of Environmental Justice in Conservation. Earners have developed a critical, interdisciplinary understanding of how justice, equity, and power intersect with conservation practice, policy, and research. Skills include applying environmental justice frameworks to conservation challenges, evaluating participatory and rights-based approaches, engaging ethically with Indigenous and local knowledge systems, and designing conservation strategies that are socially just, inclusive, and accountable.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/environmental-justice-in-conservation-from-principles-to-practice
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including readings, and activities, demonstrating the ability to: - Explain core dimensions of environmental justice, including distributive, procedural, recognitional, structural, and ecological justice - Critically analyze how historical and contemporary systems of power and inequality shape conservation outcomes - Evaluate participatory, rights-based, and safeguards-based approaches in conservation planning - Apply ethical frameworks such as Free, Prior, and Informed Consent (FPIC) to conservation contexts - Design justice-driven conservation strategies that integrate equity, accountability, and community-defined measures of success - Earn a B- (80%) or better on the capstone - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling)
type: BadgeClass

id: https://api.badgr.io/public/badges/pN7dZrUbRKCqs3u3rO_bLg
name: R Boot Camp for Ecologists & Wildlife Biologists - STANDARD Copy
image:
  id: https://badges.parchment.com/public/badges/pN7dZrUbRKCqs3u3rO_bLg/image
achievement type: Course
description: This badge recognizes the successful completion of the R Boot Camp for Ecologists & Wildlife Biologists. Earners have gained foundational skills in R and RStudio, with a focus on ecological and wildlife-related applications. Skills include importing, cleaning, and transforming ecological datasets, managing relational data, and producing publication-quality data visualizations using ggplot2.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
alignment:
  target name: Rstudio
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/34659
  target description: RStudio is a tailored IDE for R programming, focusing on statistical analysis and data visualization.
  target framework: TALENT_NEURON
  target code: TN-34659
alignment:
  target name: R Programming Language
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/33897
  target description: R Programming Language is an open-source platform for statistical computing and graphics, enabling data manipulation, calculation, and graphical display.
  target framework: TALENT_NEURON
  target code: TN-33897
alignment:
  target name: Data cleaning
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/33376
  target description: Data cleaning refers to the process of detecting and correcting errors, inconsistencies, and inaccuracies in datasets to enhance data quality and reliability for analysis.
  target framework: TALENT_NEURON
  target code: TN-33376
alignment:
  target name: Descriptive statistics
  target url: https://centerforwildlifestudies.badges.parchment.com/skills/talent-neuron/46677
  target description: Descriptive statistics are methods used to summarize, organize, and present data effectively, encompassing measures of central tendency, variability, and visual displays such as charts and histograms.
  target framework: TALENT_NEURON
  target code: TN-46677
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/r-bootcamp
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all eight modules of the course, including all exercises, which require learners to demonstrate the ability to: - Install and operate R and RStudio - Import, organize, and tidy ecological datasets - Apply R functions to perform descriptive statistics and data transformations - Join and analyze relational datasets - Create and present ecological data visually using _ggplot2_ - Earn a B- (80%) or better on the final exam - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/X4C_VKYOQiWSAdU16_dDJQ
name: Wildlife Capture and Chemical Immobilization (Online)
image:
  id: https://badges.parchment.com/public/badges/X4C_VKYOQiWSAdU16_dDJQ/image
description: This badge recognizes successful completion of Wildlife Capture and Chemical Immobilization. Learners develop foundational competencies in planning and executing wildlife capture and chemical immobilization activities while prioritizing animal welfare, human safety, and ethical research and management practices. Coursework covers capture equipment and delivery systems, pharmacology of immobilization drugs, dosage calculation, species-specific considerations, safety protocols, patient monitoring, biological sample collection, and post-capture care. Learners apply best practices for handling wildlife during capture operations and demonstrate the ability to support research, conservation, and animal care activities in field and applied settings.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/wcci-field-2024
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Select appropriate capture equipment and drug delivery systems for specific capture scenarios. - Determine appropriate immobilization drugs and calculate accurate dosages by species. - Apply safety protocols for drug handling, capture operations, and chemical immobilization. - Monitor immobilized animals and demonstrate proper patient care. - Collect biological tissue samples for research and disease monitoring. - Fit animals with radio collars or other tracking tags. - Administer vaccinations, antibiotics, and reversal agents as appropriate. ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/Szx7pPByR5aTxWsGXWwNbQ
name: Forest & Habitat Measurements - STANDARD
image:
  id: https://badges.parchment.com/public/badges/Szx7pPByR5aTxWsGXWwNbQ/image
image alt text: Forest & Habitat Measurements - STANDARD badge image
description: This badge recognizes successful completion of Multivariate Ecological Community Analysis I. Earners can distinguish univariate from multivariate analyses, prepare ecological datasets for multivariate analysis, and select appropriate distance measures based on ecological and statistical properties. Learners gain proficiency in five guided ordination techniques—weighted averaging (WA), polar ordination (PO), canonical correspondence analysis (CCA), redundancy analysis (RDA), and fuzzy set ordination (FSO)—and learn how to interpret ordination diagrams. Coursework includes hands-on analysis using PC-ORD software, with optional exercises in R.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/forest-and-habitat-measurements
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied assignments demonstrating the ability to: - Apply numerical literacy principles to vegetation measurement and interpretation - Collect accurate spatial and field data using surveying tools and techniques - Measure and quantify vegetation structure, density, cover, basal area, and biomass - Scale individual tree measurements to stand-level estimates of volume and productivity - Apply fixed-area and variable-radius sampling methods appropriately - Summarize and interpret vegetation data to support research, monitoring, or management decisions - Earn a C- (70%) or better in the course - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/5BAcmp-jTluMxIQoT7t72w
name: Wildlife Law & Policy - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/5BAcmp-jTluMxIQoT7t72w/image
image alt text: Wildlife Law & Policy - PREMIUM badge image
description: This badge recognizes the successful completion of Introduction to U.S. Wildlife Law & Policy. Earners have developed a foundational understanding of the structure, implementation, and impact of wildlife policy in the United States. Skills include analyzing major wildlife laws and agencies, evaluating policy effectiveness, and examining how legislation influences wildlife conservation and management decisions across terrestrial and marine systems.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/us-wildlife-policy
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied assignments demonstrating the ability to: - Explain the foundations and structure of U.S. wildlife policy - Differentiate between types of wildlife laws, policies, and governing agencies - Analyze the motivations and limitations behind wildlife policy decisions - Evaluate the purpose and effectiveness of major U.S. wildlife laws, including the Lacey Act, Migratory Bird Treaty Act, Endangered Species Act, and Marine Mammal Protection Act - Assess wildlife policy applications related to species protection, habitat conservation, and marine resource management - Critically discuss policy challenges and implications for wildlife management and conservation - Earn a C- (70%) or better in the course - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Conservation Planning: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/c5yv7unwQ8SOu94rCdDXSQ
name: Facilitation 101 for Conservation Professionals - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/c5yv7unwQ8SOu94rCdDXSQ/image
image alt text: Facilitation 101 for Conservation Professionals - PREMIUM badge image
description: This badge recognizes the successful completion of Facilitation 101 for Conservation Professionals. Earners have developed foundational facilitation skills to support effective meetings, workshops, and collaborative processes in conservation contexts. Skills include designing agendas, guiding group discussions, applying adult learning principles, navigating conflict, fostering creativity, and helping teams clarify goals and strategies. Participants gain practical experience facilitating exercises virtually.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/facilitation-101-for-conservation-professionals
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied facilitation activities demonstrating the ability to: - Explain core principles of facilitation and adult learning - Prepare and design effective meeting agendas aligned with clear objectives - Facilitate group processes involving diverging and converging discussions - Apply facilitation techniques such as paraphrasing, summarizing, questioning, and encouraging participation - Navigate conflict and manage difficult participants constructively - Design and facilitate creative brainstorming and decision-making exercises - Develop and document a Theory of Change and results chains - Facilitate analyze-and-adapt (“pause and reflect”) processes - Design and lead a structured one-day workshop agenda - Earn a B- (80%) or better on the final project - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Conservation Planning: B- (80%) or better on the final assessment earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/cN5la4xVTs27xJPMsAmjcA
name: Facilitation 101 for Conservation Professionals - STANDARD
image:
  id: https://badges.parchment.com/public/badges/cN5la4xVTs27xJPMsAmjcA/image
image alt text: Facilitation 101 for Conservation Professionals - PREMIUM badge image
description: This badge recognizes the successful completion of Facilitation 101 for Conservation Professionals. Earners have developed foundational facilitation skills to support effective meetings, workshops, and collaborative processes in conservation contexts. Skills include designing agendas, guiding group discussions, applying adult learning principles, navigating conflict, fostering creativity, and helping teams clarify goals and strategies. Participants gain practical experience in facilitating virtual exercises.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/facilitation-101-for-conservation-professionals
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied facilitation activities demonstrating the ability to: - Explain core principles of facilitation and adult learning - Prepare and design effective meeting agendas aligned with clear objectives - Facilitate group processes involving diverging and converging discussions - Apply facilitation techniques such as paraphrasing, summarizing, questioning, and encouraging participation - Navigate conflict and manage difficult participants constructively - Design and facilitate creative brainstorming and decision-making exercises - Develop and document a Theory of Change and results chains - Facilitate analyze-and-adapt (“pause and reflect”) processes - Design and lead a structured one-day workshop agenda - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/iYP63-iYTbK7vaNCbN2xYQ
name: Miradi Basics for Conservation Practitioners - STANDARD
image:
  id: https://badges.parchment.com/public/badges/iYP63-iYTbK7vaNCbN2xYQ/image
image alt text: Facilitation 101 for Conservation Professionals - PREMIUM badge image
description: This badge recognizes the successful completion of Miradi Basics for Conservation Practitioners. Earners have developed practical skills in using Miradi to plan, implement, and manage conservation projects using a full-cycle adaptive management approach. Skills include building situation models, developing theories of change, assessing threats and target viability, creating work plans, and designing monitoring systems to track progress toward conservation goals. Participants also gain experience collaborating within Miradi and integrating project data with external tools such as Excel and Power BI.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/miradi-basics-for-conservation-practitioners
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules and hands-on exercises, demonstrating the ability to: - Build and manage conservation project content in Miradi - Develop situation models and theories of change - Assess target viability and identify key threats - Create work plans aligned with SMART goals and objectives - Design monitoring plans to evaluate conservation outcomes - Apply best practices for data quality and team collaboration in Export and work with Miradi data in external tools (e.g., Excel, Power BI) - Develop and document a Theory of Change and results chains - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/sEpOt70YQOGA3hb6dO-i3w
name: Miradi Basics for Conservation Practitioners - BASIC
image:
  id: https://badges.parchment.com/public/badges/sEpOt70YQOGA3hb6dO-i3w/image
image alt text: Facilitation 101 for Conservation Professionals - PREMIUM badge image
description: This badge recognizes the successful completion of Miradi Basics for Conservation Practitioners. Earners have developed practical skills in using Miradi to plan, implement, and manage conservation projects using a full-cycle adaptive management approach. Skills include building situation models, developing theories of change, assessing threats and target viability, creating work plans, and designing monitoring systems to track progress toward conservation goals. Participants also gain experience collaborating within Miradi and integrating project data with external tools such as Excel and Power BI.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/miradi-basics-for-conservation-practitioners
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules and hands-on exercises, demonstrating the ability to: - Build and manage conservation project content in Miradi - Develop situation models and theories of change - Assess target viability and identify key threats - Create work plans aligned with SMART goals and objectives - Design monitoring plans to evaluate conservation outcomes - Apply best practices for data quality and team collaboration in Export and work with Miradi data in external tools (e.g., Excel, Power BI) - Develop and document a Theory of Change and results chains - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better earns 1 credit toward certification (Category F: Statistical Modeling) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/EGv6VmCyTOixQtLb5-bcyQ
name: Geospatial Analysis with Google Earth Engine - STANDARD
image:
  id: https://badges.parchment.com/public/badges/EGv6VmCyTOixQtLb5-bcyQ/image
image alt text: Geospatial Analysis with Google Earth Engine - STANDARD badge image
description: add
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/geospatial-analysis-with-google-earth-engine
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Install Python and supporting tools (Conda, Jupyter, IDEs). - Write and execute Python code interactively. - Assign variables, manipulate data types, and use functions. - Apply coding fundamentals, including conditionals, loops, and custom functions. - Ingest and manipulate data using Pandas dataframes. - Perform basic data wrangling (reshaping, subsetting, modifying values). - Create visualizations (scatter plots, histograms, basic charts). - Apply introductory machine learning models with scikit-learn. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/CV7nvUzpRyqHfd5eYqX8Ng
name: Geospatial Analysis with Google Earth Engine - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/CV7nvUzpRyqHfd5eYqX8Ng/image
image alt text: Geospatial Analysis with Google Earth Engine - STANDARD badge image
description: add
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/geospatial-analysis-with-google-earth-engine
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Install Python and supporting tools (Conda, Jupyter, IDEs). - Write and execute Python code interactively. - Assign variables, manipulate data types, and use functions. - Apply coding fundamentals, including conditionals, loops, and custom functions. - Ingest and manipulate data using Pandas dataframes. - Perform basic data wrangling (reshaping, subsetting, modifying values). - Create visualizations (scatter plots, histograms, basic charts). - Apply introductory machine learning models with scikit-learn. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category F: Basic Statistics) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/NaFtXEMUQp2LQ8UUom-Pcg
name: Miradi Basics for Conservation Practitioners - STANDARD
image:
  id: https://badges.parchment.com/public/badges/NaFtXEMUQp2LQ8UUom-Pcg/image
image alt text: Biology and Ecology of Sharks and Their Relatives - Online & Field badge image
description: a
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/miradi-basics-for-conservation-practitioners
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the online course, including all lectures, readings, and activities. - Actively participate in a 3-day field experience aboard a research vessel. - Demonstrate the ability to: - Identify major groups of sharks and explain their evolutionary history - Describe shark reproductive strategies and life history traits - Explain the ecological roles and behaviors of sharks - Interpret conservation and management issues related to shark migration, fisheries, and ecosystem function - Earn a C- (70%) or better on the final project ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Continuing Education: Course completion earns 16 CEUs - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final project earns 1 credit toward certification in Wildlife Management and Biology
type: BadgeClass

id: https://api.badgr.io/public/badges/pY2Z0mMcSbiY_Ujp8udQMw
name: Financing Conservation - BASIC
image:
  id: https://badges.parchment.com/public/badges/pY2Z0mMcSbiY_Ujp8udQMw/image
image alt text: Financing Conservation - BASIC badge image
description: This badge recognizes the successful completion of Introduction to Conservation Finance. Earners have developed a multidisciplinary understanding of conservation finance, including the tools, strategies, and policies used to support biodiversity, climate, and water conservation. Skills include evaluating conservation finance mechanisms, assessing environmental market approaches, analyzing challenges and critiques, and applying conservation finance concepts to real-world scenarios.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/conservation-finance
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the online course, including all lectures, readings, and activities. - Demonstrate the ability to: - Explain the similarities and differences among conservation finance tools and strategies - Identify appropriate finance mechanisms for different conservation scenarios - Evaluate metrics used to assess environmental and conservation outcomes - Analyze critiques, challenges, and limitations of conservation finance approaches - Examine the roles of policy, public funding, and private investment in conservation finance - Communicate conservation finance concepts effectively through discussions and applied activities - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Continuing Education: Course completion earns 16 CEUs - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final project earns 1 credit toward certification in Wildlife Management and Biology
type: BadgeClass

id: https://api.badgr.io/public/badges/6tPQNiadQySXFBMg268dqg
name: Plant Identification for Wildlife Biologists - STANDARD
image:
  id: https://badges.parchment.com/public/badges/6tPQNiadQySXFBMg268dqg/image
image alt text: Plant Identification for Wildlife Biologists - STANDARD badge image
description: Earners of this badge have demonstrated foundational skills in plant identification and classification used in wildlife biology, ecology, and conservation. Participants explored major plant groups, plant structure and terminology, and methods for identifying trees, shrubs, and herbaceous plants using technical plant keys. Through hands-on activities, learners practiced collecting, documenting, photographing, and organizing plant specimens and developed a digital plant collection for a selected study area. Earners can apply these skills to habitat assessment, wildlife management, ecological fieldwork, and environmental research.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/plant-identification
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify and classify major plant groups and common plant families - Describe plant structures and terminology used in plant identification - Use technical plant keys to systematically identify plant species - Collect, press, photograph, and document plant specimens - Organize and curate a digital plant collection for a selected study area - Submit all required assignments and exercises related to plant identification and classification - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/nsMAQUAfRNiHFsWOSROetA
name: Plant Identification for Wildlife Biologists - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/nsMAQUAfRNiHFsWOSROetA/image
image alt text: Plant Identification for Wildlife Biologists - PREMIUM badge image
description: Earners of this badge have demonstrated foundational skills in plant identification and classification used in wildlife biology, ecology, and conservation. Participants explored major plant groups, plant structure and terminology, and methods for identifying trees, shrubs, and herbaceous plants using technical plant keys. Through hands-on activities, learners practiced collecting, documenting, photographing, and organizing plant specimens and developed a digital plant collection for a selected study area. Earners can apply these skills to habitat assessment, wildlife management, ecological fieldwork, and environmental research.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/plant-identification
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Identify and classify major plant groups and common plant families - Describe plant structures and terminology used in plant identification - Use technical plant keys to systematically identify plant species - Collect, press, photograph, and document plant specimens - Organize and curate a digital plant collection for a selected study area - Submit all required assignments and exercises related to plant identification and classification - Complete the final digital plant collection project - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/57KMOLAaTYSyV9vXd93gZw
name: Sea Turtle Ecology, Conservation, & Research Methods - STANDARD
image:
  id: https://badges.parchment.com/public/badges/57KMOLAaTYSyV9vXd93gZw/image
image alt text: Forest & Habitat Measurements - STANDARD badge image
description: a
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/sea-turtle-intro
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied assignments demonstrating the ability to: - Apply numerical literacy principles to vegetation measurement and interpretation - Collect accurate spatial and field data using surveying tools and techniques - Measure and quantify vegetation structure, density, cover, basal area, and biomass - Scale individual tree measurements to stand-level estimates of volume and productivity - Apply fixed-area and variable-radius sampling methods appropriately - Summarize and interpret vegetation data to support research, monitoring, or management decisions - Earn a C- (70%) or better in the course - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/-MB4d32wTlWTZlDf9Cluag
name: Sea Turtle Ecology, Conservation, & Research Methods - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/-MB4d32wTlWTZlDf9Cluag/image
image alt text: Forest & Habitat Measurements - STANDARD badge image
description: a
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/sea-turtle-intro
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied assignments demonstrating the ability to: - Apply numerical literacy principles to vegetation measurement and interpretation - Collect accurate spatial and field data using surveying tools and techniques - Measure and quantify vegetation structure, density, cover, basal area, and biomass - Scale individual tree measurements to stand-level estimates of volume and productivity - Apply fixed-area and variable-radius sampling methods appropriately - Summarize and interpret vegetation data to support research, monitoring, or management decisions - Earn a C- (70%) or better in the course - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs - ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/ySBM69aaTl2gvxoMmOnVaA
name: Geospatial Modeling in QGIS and R - BASIC
image:
  id: https://badges.parchment.com/public/badges/ySBM69aaTl2gvxoMmOnVaA/image
image alt text: Geospatial Modeling in QGIS and R - PREMIUM badge image
description: This badge recognizes successful completion of Geospatial Modeling with QGIS and R. Earners gain skills in processing and analyzing spatial data to study wildlife home range and habitat use. Learners use QGIS, R, and the Geospatial Modeling Environment (GME) to create and transform spatial data, generate shape files, and estimate home ranges. They apply raster land cover and remote sensing data to conduct vegetation analysis and compare used vs. available habitats. Badge earners can integrate spatial data layers, calculate geometry, and conduct habitat assessments to inform population and habitat management decisions.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/geospatial-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including applied exercises in QGIS, R, and GME. - Demonstrate the ability to: - Download and prepare spatial datasets from online sources. - Create, manage, and transform vector data (points, shape files, coordinate systems). - Process raw point location data to calculate home ranges. - Use QGIS and GME to analyze and visualize home range data. - Apply raster data for vegetation and habitat analysis. - Distinguish between used and available habitats and conduct statistical comparisons. - Submit assignments or projects demonstrating home range and habitat analysis using QGIS and R. - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS • CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit • ESA Ecologist at any level: B- (80%) or better on the final exam earns 1 credit toward certification • TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) • TWS Continuing Education: Course completion earns 16 CEUs • ESA Continuing Education: Course completion earns 4 CEUs in Category I(a): Scientific Education and Training
type: BadgeClass

id: https://api.badgr.io/public/badges/0GxDxrDETZCJY7JmhKf7YA
name: Wildlife Capture and Chemical Immobilization - STANDARD
image:
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image alt text: Wildlife Capture and Chemical Immobilization - STANDARD badge image
description: This badge recognizes successful completion of Wildlife Capture and Chemical Immobilization. Learners develop foundational competencies in planning and executing wildlife capture and chemical immobilization activities while prioritizing animal welfare, human safety, and ethical research and management practices. Coursework covers capture equipment and delivery systems, pharmacology of immobilization drugs, dosage calculation, species-specific considerations, safety protocols, patient monitoring, biological sample collection, and post-capture care. Learners apply best practices for handling wildlife during capture operations and demonstrate the ability to support research, conservation, and animal care activities in field and applied settings.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/wcci-field-2024
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Select appropriate capture equipment and drug delivery systems for specific capture scenarios. - Determine appropriate immobilization drugs and calculate accurate dosages by species. - Apply safety protocols for drug handling, capture operations, and chemical immobilization. - Monitor immobilized animals and demonstrate proper patient care. - Collect biological tissue samples for research and disease monitoring. - Fit animals with radio collars or other tracking tags. - Administer vaccinations, antibiotics, and reversal agents as appropriate. - Earn a B- (80%) or better on the final exam. ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/_ZsiKp33Qn2a3YJQS6DuNw
name: Bayesian Causal Networks for Complex Multivariate Systems - STANDARD
image:
  id: https://badges.parchment.com/public/badges/_ZsiKp33Qn2a3YJQS6DuNw/image
image alt text: Bayesian Causal Networks for Complex Multivariate Systems - STANDARD badge image
achievement type: Course
description: This badge recognizes successful completion of Bayesian Causal Networks for Complex Multivariate Systems. Earners develop proficiency in creating, calibrating, and updating Bayesian Causal Network (BCN) models to represent causal relationships in complex ecological systems. Skills include using Netica software to build influence diagrams, decision nets, and Bayesian networks; performing sensitivity analysis; and applying scenario testing to predict system responses. Badge earners can design and refine BCN models to identify leverage points for intervention and support strategic ecological decision-making.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/bayesian-causal-network-modeling
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, including exercises and required surveys. - Demonstrate the ability to: - Explain Bayesian Causal Network (BCN) concepts and their applications to complex multivariate systems. - Research and document frameworks for BCN modeling relevant to ecological problems. - Create influence diagrams and Decision Nets in Netica. - Build, calibrate, and simplify BCN models. - Conduct sensitivity analysis and scenario testing to assess system behavior. - Update BCN models with new data to refine predictions. - Earn a C- (70%) or better on the final exam ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Applied Quantitative Ecology: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/rXYktyFbQXecZl1saSYsLQ
name: Wildlife Law & Policy - STANDARD
image:
  id: https://badges.parchment.com/public/badges/rXYktyFbQXecZl1saSYsLQ/image
image alt text: Wildlife Law & Policy - PREMIUM badge image
description: This badge recognizes the successful completion of Introduction to U.S. Wildlife Law & Policy. Earners have developed a foundational understanding of the structure, implementation, and impact of wildlife policy in the United States. Skills include analyzing major wildlife laws and agencies, evaluating policy effectiveness, and examining how legislation influences wildlife conservation and management decisions across terrestrial and marine systems.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/us-wildlife-policy
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all course modules, exercises, and applied assignments demonstrating the ability to: - Explain the foundations and structure of U.S. wildlife policy - Differentiate between types of wildlife laws, policies, and governing agencies - Analyze the motivations and limitations behind wildlife policy decisions - Evaluate the purpose and effectiveness of major U.S. wildlife laws, including the Lacey Act, Migratory Bird Treaty Act, Endangered Species Act, and Marine Mammal Protection Act - Assess wildlife policy applications related to species protection, habitat conservation, and marine resource management - Critically discuss policy challenges and implications for wildlife management and conservation - Earn a C- (70%) or better in the course - Complete all required course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - CWS professional certificate in Conservation Planning: B- (80%) or better on the final exam earns 1 credit - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final exam earns 1 credit toward certification (in Category G: Quantitative Sciences) - TWS Continuing Education: Course completion earns 16 CEUs
type: BadgeClass

id: https://api.badgr.io/public/badges/lAummMylSnCILGniBcapzg
name: Financing Conservation - PREMIUM
image:
  id: https://badges.parchment.com/public/badges/lAummMylSnCILGniBcapzg/image
image alt text: Financing Conservation - BASIC badge image
description: This badge recognizes the successful completion of Introduction to Conservation Finance. Earners have developed a multidisciplinary understanding of conservation finance, including the tools, strategies, and policies used to support biodiversity, climate, and water conservation. Skills include evaluating conservation finance mechanisms, assessing environmental market approaches, analyzing challenges and critiques, and applying conservation finance concepts to real-world scenarios.
issuer: https://api.badgr.io/public/issuers/W4wxPjo3TNqLBnuT1jMjfQ
criteria:
  id: https://www.centerforwildlifestudies.org/courses/p/conservation-finance
  narrative: ### EARNING CRITERIA To earn this badge, learners must: - Complete all modules of the online course, including all lectures, readings, and activities. - Demonstrate the ability to: - Explain the similarities and differences among conservation finance tools and strategies - Identify appropriate finance mechanisms for different conservation scenarios - Evaluate metrics used to assess environmental and conservation outcomes - Analyze critiques, challenges, and limitations of conservation finance approaches - Examine the roles of policy, public funding, and private investment in conservation finance - Communicate conservation finance concepts effectively through discussions and applied activities - Earn a C- (70%) or better on the final project - Complete all course surveys ### COURSE DELIVERY Online ### BADGE BENEFITS - TWS Continuing Education: Course completion earns 16 CEUs - TWS Associate or Certified Wildlife Biologist®: C- (70%) or better on the final project earns 1 credit toward certification in Wildlife Management and Biology
type: BadgeClass