📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI-Powered Econometric Forecasting & Causal Inference, from foundations to a certified capstone project.
Outline
Construct multi‑source panel datasets from World Bank and macro‑economic indicators • Implement Multiple Imputation by Chained Equations (MICE) for missing macro data • Engineer temporal and policy‑related features for causal analysis
Outline
Apply Double Machine Learning (EconML) to estimate treatment effects • Build Causal Forest models to uncover heterogeneous regional impacts • Execute Synthetic Control using Bayesian Structural Time Series for policy comparison
Outline
Conduct placebo tests and falsification checks • Analyse SHAP values for interpretability • Validate assumptions with balance and overlap diagnostics
Outline
Create interactive policy simulation tools in Streamlit • Generate counterfactual scenario analyses • Design publication‑grade visualizations with Plotly
Outline
Structure code notebooks for reproducibility • Export results to LaTeX/Word for journal submission • Version‑control datasets and scripts with Git
Outline
Craft policy briefs that translate causal findings into actionable recommendations • Prepare presentation decks for academic and governmental audiences • Develop grant‑proposal sections showcasing methodological rigor
Earn government-registered certification in AI-Powered Econometric Forecasting & Causal Inference
e-Certificate and e-Marksheet issued on successful completion.
