Table of Contents

Introduction to Python, Numpy and Pandas

  1. A Whirlwind Tour of Python - Jake VanderPlas

  2. Python Data Science Handbook - Jake VanderPlas

  3. From Python to Numpy - Nicolas P. Rougier

  4. 100 numpy exercises - Nicolas P. Rougier

  5. A Concrete Introduction to Probability (using Python) - Peter Norvig

Introduction to Probability and Statistics (videos and books)

  1. Khan Academy’s statistics and probability course

  2. Bayesian Statistics the Fun Way - Will Kurt

  3. Think Stats - Allen B. Downey

  4. Think Bayes - Allen B. Downey

  5. The Art of Data Science: A Guide for Anyone Who Works with Data - Roger D. Peng, Elizabeth Matsui

Probabilistic Programming

  1. Probabilistic Programming & Bayesian Methods for Hackers - Cam Davidson-Pilon

  2. Bayesian Analysis with Python - Osvaldo Martin

MOOCs

  1. Harvard’s Statistics 110: Probability

  2. Duke’s Statistics with R Specialization

  3. MITx’s Statistics and Data Science MicroMasters

Books

  1. Introduction to Probability - Joseph K. Blitzstein, Jessica Hwang

  2. Doing Bayesian Data Analysis: A Tutorial Introduction with R - John K. Kruschke

  3. Statistical Rethinking - Richard McElreath

  4. Probability Theory: The Logic of Science - E.T. Jaynes

  5. Aubrey Clayton lectures on the key chapters of Probability Theory The Logic of Science

  6. Bayesian Data Analysis - Andrew Gelman

Papers and Thesis

  1. Automating Inference, Learning, and Design using Probabilistic Programming - Tom Rainforth

  2. A Conceptual Introduction to Hamiltonian Monte Carlo

  3. The Markov Chain Monte Carlo Revolution