AI-Enhanced Learning
4 AI tutors, 4 learning styles. Each tutor is a customized Google Gemini Gem with a distinct pedagogical approach to causal inference.
Recommended for first-time learners
Your step-by-step guide through causal inference. Breaks down complex concepts into manageable pieces, provides worked examples, and checks understanding at each stage. Ideal for working through the material chapter by chapter.
Best for: Structured learning, homework help, building intuition
Start Learning →For deeper understanding
Teaches through questions rather than answers. Challenges your assumptions about causation, pushes you to think about identification strategies, and helps you develop the critical thinking skills needed for research design.
Best for: Critical thinking, research design, exam preparation
ForthcomingFor hands-on learners
Learns by doing. Starts with Python code and real data, then builds up to the theory. Helps you modify and extend the chapter notebooks, run your own analyses, and understand causal methods through computational experimentation.
Best for: Python practice, data analysis, extending examples
ForthcomingFor test preparation
Focused on assessment readiness. Provides practice questions, identifies knowledge gaps, and drills key concepts and formulas. Covers the distinction between methods, when each applies, and common exam pitfalls in causal inference courses.
Best for: Exam review, self-assessment, concept retention
ForthcomingPick the learning style that matches your needs and goals.
Ask about any chapter, concept, or dataset. The tutor knows the full curriculum.
Follow the tutor's guidance, run code in Colab, and build your causal inference skills.