Data Science Courses & Textbooks

General Data Science

STAT 447: Data Science Programming Methods by Dirk Eddelbuettel

IPUMS Tutorials - how to use IPUMS data, online analysis tools

Bayesian Data Analysis course by Aki Vehtari

A Programmer’s Introduction to Mathematics by Jeremy Kun

Statistical Rethinking: A Bayesian Course with Examples in R and Stan by Richard McElreath

Data Science and Society by Chris Bail (Duke)

Mathematics for Machine Learning by Garrett Thomas

Introduction to Data Science: Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry

Harvard CS197: AI Research Experiences: Learn to do applied deep learning research by Professor Pranav Rajpurkar

Algebra, Topology, Differential Calculus, and Optimization Theory For Computer Science and Machine Learning by Gallier and Quaintance

DSC 223: Introduction to Data Science by Tyler George

The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Hastie, Tibshirani, Friedman

Coding for Economists by Arthur Turrell & Others

Python, R, and Stata Implementation of Statistical Methods

Code and Data for the Social Sciences: A Practitioner’s Guide by Gentzkow & Shapiro

ECON 607 - Data Science for Economists by Grant McDermott

R, Stata, and Python Resources by Gabors Data Analysis

Resources for Learning Python, R, SQL, and Data Science by Data Umbrella

Kaggle Learn Guides for Data Science (curated by Avi Kumar Talavia)

Data Science and Statistics Cheat Sheets, Machine Learning Lecture Notes, and more by Merve Noyan

Python

Style Guide for Python Code by Rossum, Warsaw, & Coghlan

Stata to Python Equivalents by Daniel M. Sullivan

Python Courses by Code Academy

Pyslackers - An open community for Python programming enthusiasts.

Python Discord

PyLadies - mentorship group with a focus on helping more women become active participants and leaders in the Python open-source community

From R to Python by Joscelin Rocha Hidalgo - a collection of Python resources geared toward someone with a background in R

Coming from R (to Python) by Arthur Turrell

Probabilistic Programming in Python by Salvatier, Wiecki, Fonnesbeck

Introduction to Economic Modeling and Data Science (in Python) by Coleman, Lyon, Perla, et al

Python for Social Science by Jean Mark Gawron

Python Resources Aggregator by UC Berkeley

Full Stack Python - Learn to Build, Deploy and Operate Python Applications by Matt Makai

Automate the Boring Stuff with Python by Al Sweigart

Selenium with Python by Baiju Muthukadan

Python project-based tutorials by (many people)

Python Numpy Tutorial (with Jupyter and Colab) by Justin Johnson

Introduction to Python and NumPy for Deep Learning by DeepMind Technologies Limited

Mapping and Data Visualization with Python by Ujaval Gandhi

From Python to Numpy by Nicolas P. Rougier - “concentrating on the migration from Python to Numpy through vectorization”

SQL

SQL for Data Analysis by udacity

SQL Tutorial by Mode

Introduction to SQL Course by DataCamp

SQL Tutorial - Full Database Course for Beginners by freeCodeCamp.org

Introduction to SQL by W3 Schools

SQL Practice Questions

8 Week SQL Challenge by Data With Danny

Practical SQL for Data Analysis by Haki Benita

SQL Tutorial by SQLZoo

R

R-Ladies Global

Nice R code blog by Rich FitzJohn and Daniel Falster

A Succinct Intro to R by Steve Haroz

STAT 545 - UBC course on R and data science

R for Stata Users by Andrade, et. al.

Text Mining with R by Silge & Robinson

RStudio Cheatsheets

The R Tidyverse Style Guide by Hadley Wickham

R for Data Science by Hadley Wickham

Intro to R by Hans H. Sievertsen - how to load, process, and visualize data in R

Applied Economics with R by Hans H. Sieversten

Regression analysis in R by Grant R. McDermott

Big Book of R by Oscar Baruffa

List of open sources books about R by Pere A. Taberner

Analyzing US Census Data: Methods, Maps, and Models in R by Kyle Walker

Best Coding Practices for R by Vikram Singh Rawat

R Markdown: The Definitive Guide by Xie, Allaire, and Grolemund

Introduction to Econometrics with R by Hanck, et. al.

Translating Stata to R by McDermott, Butts, Nick HK

R Function A Day by Indrajeet Patil - collections of 365 tweets about R functions

Statistics lectures using R by Amelia McNamara

Introduction to Data Science in the Tidyverse by McNamara and Wickham

A Road Map for historians of economics to learn R by Aurélien Goutsmedt

Hands-On Programming with R by Garrett Grolemund - emphasis on simulation and vectorizations

Using R for Introductory Econometrics 2nd edition by Florian Heiss - R coding companion to Wooldridge’s textbook

Overview of Econometrics Packages in R by Zeileis and McDermott

Coding style, coding etiquette (in R) by Salmon and Dervieux

R for Stata Users by Matthieu Gomez

Resources for self-guided learning by R-Ladies NYC

Introduction to GitHub Actions to R users by Beatriz Milz

An Introduction to Statistical Learning with Applications in R by James, et. al.

Writing Functions in R by Cosima Meyer

Stata

Learning Stata for econ research aggregator by Wayne Aaron Sandholtz

Stata Coding Guide by Julian Reif

Development Research in Practice (Stata Style Guide) by DIME Analytics

Applied Econometrics in Stata by Jack Blundell

Stata Cheat Sheets

Programming with Stata by Kluender and Marx

Stata Workflow Guide by Asjad Naqvi

Maximum Likelihood Estimation (MLE) in Stata by Asjad Naqvi

Coding Style Guide by Michael Stepner

Microeconometrics Using Stata by Cameron and Trivedi

Tips for managing large-scale datasets efficiently in Stata by Pere A. Taberner

The Stata Guide (aggregate) by Asjad Naqvi

Stata Style Guide by Miklos Koren

Stata Guide by Sean Higgins

UCLA Stata Learning Modules

Matlab

MATLAB/R Reference by David Hiebeler

LaTeX

LaTeX for Beginners, 5th Edition

LaTeX Table Hints and Tips by Adrian P. Robson

Short Math Guide for LaTeX by Downes, updated by Beeton

The Not So Short Introduction to LaTeX by Tobias Oetiker

Data Viz

An Economist’s Guide to Visualizing Data by Jonathan A. Schwabish

Telling Stories With Data by Rohan Alexander

Data Visualization: A Practical Introduction by Kieran Healy

Data Visualization Checklist by NickCH-K

Hands-On Data Visualization Dougherty and Ilyankou

Git + GitHub

Git and GitHub chapter of R Packages by Hadley Wickham and Jenny Bryan

GitHub Replication Template by Dequette

Git: A Guide for Economists by Frank Pinter

Git and GitHub for R by Jenny Bryan and others

GitHub Project Example with Stata Coding Style Guide by Michael Stepner

How to Use Git/GitHub with R by David Keyes

Git Cheat Sheet for Data Scientists by Kessie Zhang

Other

QuantEcon - open source code workshops and resources for economic modeling

Computational Thinking for Social Scientists by Jae Yeon Kim

Coding for Economists: A Language-Agnostic Guide to Programming for Economists by Ljubica Ristovska

Working with Large Data Technical Report by Gomolka, Blaschke, Hirsch

More Data Analysis Case Studies and Resources for R and Python by Gabors Data Analysis

Julia Bootcamp by Cameron Pfiffer

Mostly Harmless Econometrics Replication Code in Stata, R, Python, and Julia by Vikram Jambulapati

Quantitative Editing: A Guide by Laura Bronner

Data Analysis Case Study codebase for R, Python, and Stata by Békés and Kézdi