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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⢠Introduction to Causal Modeling: Basics of causal inference, causal models, and their importance
⢠Causal Graphs and Directed Acyclic Graphs (DAGs): Understanding causal graphs, nodes, edges, and conditional independence
⢠Do-Calculus and Interventions: Concepts of interventions, do-calculus, and its applications
⢠Parametric and Non-Parametric Causal Models: Differences, advantages, and disadvantages of various causal modeling techniques
⢠Causal Inference with Propensity Score Matching: Propensity score-based methods and their implementation
⢠Instrumental Variables and Instrumental Variable Regression: IV estimation, Two-Stage Least Squares (2SLS), and limitations
⢠Causal Bias and Sensitivity Analysis: Identifying and addressing potential biases, robustness checks, and sensitivity analysis
⢠Regression Discontinuity Designs: Regression discontinuity analysis, sharp and fuzzy designs
⢠Difference-in-Differences (DiD) Estimation: DiD design, parallel trends assumption, and extensions
⢠Advanced Topics in Causal Inference: Panel data models, Bayesian methods, and machine learning approaches in causal modeling
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