Professional Certificate in Effective Causal Modeling
-- ViewingNowThe Professional Certificate in Effective Causal Modeling is a comprehensive course designed to equip learners with the essential skills needed to analyze and interpret complex data sets. This course is vital for professionals working in data science, analytics, research, and other fields that require advanced data analysis skills.
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โข Introduction to Causal Modeling: Basics of causal inference, causal models, and their importance
โข Causal Graphs and Directed Acyclic Graphs (DAGs): Understanding causal graphs, nodes, edges, and conditional independence
โข Do-Calculus and Interventions: Concepts of interventions, do-calculus, and its applications
โข Parametric and Non-Parametric Causal Models: Differences, advantages, and disadvantages of various causal modeling techniques
โข Causal Inference with Propensity Score Matching: Propensity score-based methods and their implementation
โข Instrumental Variables and Instrumental Variable Regression: IV estimation, Two-Stage Least Squares (2SLS), and limitations
โข Causal Bias and Sensitivity Analysis: Identifying and addressing potential biases, robustness checks, and sensitivity analysis
โข Regression Discontinuity Designs: Regression discontinuity analysis, sharp and fuzzy designs
โข Difference-in-Differences (DiD) Estimation: DiD design, parallel trends assumption, and extensions
โข Advanced Topics in Causal Inference: Panel data models, Bayesian methods, and machine learning approaches in causal modeling
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