Prerequisites and Outline

In this section we'll detail the prerequisites and course outline, listed below
  • Prerequisites: 
    • Familiarity with PyData stack
    • Basics of probability
  • Outline: 
    1. Motivation
    2. How it all fits together
    3. Primer on Probability Distributions
    4. Primer on Bayes Theorem
    5. Overview of Tools: NumPy, PyMC, ArviZ, Aesara
    6. Bayesian Linear Regression
    7. Samplers, Diagnostics, Convergences
    8. Hierarchical Models
    9. Bayesian Workflow