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Data Science Courses & Textbooks

Free courses and textbooks for Python, R, SQL, Stata, LaTeX, data viz, Git, and general data science.

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General Data Science
STAT 447: Data Science Programming Methods
by Dirk Eddelbuettel
Course on programming methods for data science.
IPUMS Tutorials
by IPUMS
How to use IPUMS data and online analysis tools.
Bayesian Data Analysis Course
by Aki Vehtari
Course with Bayesian approaches.
A Programmer's Introduction to Mathematics
by Jeremy Kun
Mathematical foundations for programmers.
Statistical Rethinking
by Richard McElreath
Bayesian course with examples in R and Stan.
Data Science and Society
by Chris Bail · Duke
Social dimensions of data science.
Mathematics for Machine Learning
by Garrett Thomas
Mathematical foundations for ML.
Introduction to Data Science
by Rafael A. Irizarry
Data analysis and prediction algorithms with R.
Harvard CS197: AI Research Experiences
by Pranav Rajpurkar · Harvard
Applied deep learning research course.
The Elements of Statistical Learning
by Hastie, Tibshirani, Friedman
Data mining, inference, and prediction.
Coding for Economists
by Arthur Turrell & others
Programming guide for economists.
Python, R, and Stata Implementation of Statistical Methods
by Multiple contributors
Implementation reference across programming languages.
ECON 607 — Data Science for Economists
by Grant McDermott
Economics-focused data science.
R, Stata, and Python Resources
by Gabors Data Analysis
Multi-language learning materials.
Resources for Learning Python, R, SQL, and Data Science
by Data Umbrella
Curated learning pathways.
Data Science and Statistics Cheat Sheets
by Merve Noyan
Reference materials and notes.
Python
Style Guide for Python Code
by Rossum, Warsaw, & Coghlan
Official Python coding standards.
Stata to Python Equivalents
by Daniel M. Sullivan
Translation guide for Stata users.
Python Courses
by Codecademy
Interactive Python programming courses.
From R to Python
by Joscelin Rocha Hidalgo
Collection of Python resources geared toward those with an R background.
Coming from R (to Python)
by Arthur Turrell
Migration guide for R users.
Probabilistic Programming in Python
by Salvatier, Wiecki, Fonnesbeck
Bayesian modeling framework.
Introduction to Economic Modeling and Data Science
by Coleman, Lyon, Perla et al.
Economics course in Python.
Python for Social Science
by Jean Mark Gawron
Social science applications.
Full Stack Python
by Matt Makai
Learn to build, deploy and operate Python applications.
Automate the Boring Stuff with Python
by Al Sweigart
Practical automation guide.
Selenium with Python
by Baiju Muthukadan
Web automation framework documentation.
Python Numpy Tutorial
by Justin Johnson · Stanford
With Jupyter and Colab.
Mapping and Data Visualization with Python
by Ujaval Gandhi
Geospatial visualization techniques.
From Python to Numpy
by Nicolas P. Rougier
Concentrating on the migration through vectorization.
SQL
SQL for Data Analysis
by Udacity
Database querying for analytics.
SQL Tutorial
by Mode
Interactive SQL learning.
Introduction to SQL Course
by DataCamp
Foundational SQL skills.
SQL Tutorial — Full Database Course for Beginners
by freeCodeCamp.org
Comprehensive video course.
Introduction to SQL
by W3Schools
Reference and tutorials.
SQL Practice Questions
by sql-practice.com
Interactive practice environment.
8 Week SQL Challenge
by Data With Danny
Structured practice challenges.
Practical SQL for Data Analysis
by Haki Benita
Applied SQL techniques.
SQL Tutorial
by SQLZoo
Interactive learning platform.
R
R-Ladies Global
by R-Ladies
Global organization of R enthusiasts.
STAT 545
by UBC
Course on R and data science.
R for Stata Users
by Andrade et al.
Translation guide for Stata users.
Text Mining with R
by Silge & Robinson
Using tidytext principles.
RStudio Cheatsheets
by RStudio
Quick reference materials.
The R Tidyverse Style Guide
by Hadley Wickham
Official style standards for tidyverse.
R for Data Science
by Hadley Wickham
Comprehensive R and data science guide.
Intro to R
by Hans H. Sievertsen
How to load, process, and visualize data.
Applied Economics with R
by Hans H. Sievertsen
Economics applications in R.
Big Book of R
by Oscar Baruffa
Comprehensive catalog of 300+ R resources.
Analyzing US Census Data
by Kyle Walker
Methods, maps, and models in R.
R Markdown: The Definitive Guide
by Xie, Allaire, Grolemund
Dynamic documents and reports.
Introduction to Econometrics with R
by Hanck et al.
Applied econometrics course.
Translating Stata to R
by McDermott, Butts, Nick HK
Comprehensive translation resource.
Hands-On Programming with R
by Garrett Grolemund
Emphasis on simulation and vectorizations.
Using R for Introductory Econometrics
by Florian Heiss
R coding companion to Wooldridge's textbook.
Overview of Econometrics Packages in R
by Zeileis, McDermott
Econometrics package survey.
R for Stata Users
by Matthieu Gomez
Translation and comparison.
An Introduction to Statistical Learning
by James et al.
With applications in R.
Stata
Learning Stata for Econ Research Aggregator
by Wayne Aaron Sandholtz
Curated resource compilation.
Stata Coding Guide
by Julian Reif
Professional coding standards.
Development Research in Practice
by DIME Analytics · World Bank
Stata Style Guide.
Applied Econometrics in Stata
by Jack Blundell
Econometric methodology.
Stata Cheat Sheets
by Stata
Official quick reference.
Programming with Stata
by Kluender, Marx · J-PAL
Workshop materials.
Stata Workflow Guide
by Asjad Naqvi
Project organization methods.
Coding Style Guide
by Michael Stepner
Professional standards documentation.
Microeconometrics Using Stata
by Cameron, Trivedi
Comprehensive reference text.
The Stata Guide (Aggregate)
by Asjad Naqvi
Comprehensive Medium series.
Stata Style Guide
by Miklos Koren
Coding conventions.
Stata Guide
by Sean Higgins
Repository-based reference.
UCLA Stata Learning Modules
by UCLA
Institutional tutorials.
LaTeX
LaTeX Table Hints and Tips
by Adrian P. Robson
Table formatting techniques.
Short Math Guide for LaTeX
by Downes, updated by Beeton
Mathematical typesetting.
The Not So Short Introduction to LaTeX
by Tobias Oetiker
Comprehensive reference.
Data Visualization
An Economist's Guide to Visualizing Data
by Jonathan A. Schwabish
Economics perspective on visualization.
Telling Stories With Data
by Rohan Alexander
Data narrative and communication.
Data Visualization: A Practical Introduction
by Kieran Healy
Applied visualization methods.
Data Visualization Checklist
by NickCH-K
Evaluation framework.
Hands-On Data Visualization
by Dougherty, Ilyankou
Interactive visualization guide.
Git + GitHub
Git and GitHub chapter of R Packages
by Hadley Wickham, Jenny Bryan
Version control for R projects.
Git: A Guide for Economists
by Frank Pinter
Economics-focused Git guide.
Happy Git with R
by Jenny Bryan et al.
Git and GitHub workflow for R.
GitHub Project Example with Stata Coding Style
by Michael Stepner
Documentation best practices.
How to Use Git/GitHub with R
by David Keyes
R-specific workflow.
Git Cheat Sheet for Data Scientists
by Kessie Zhang
Quick reference guide.
Matlab & Other Languages
MATLAB/R Reference
by David Hiebeler
Cross-language comparison.
QuantEcon
by QuantEcon
Open source code workshops and resources for economic modeling.
Mostly Harmless Econometrics Replication Code
by Vikram Jambulapati
Stata, R, Python, and Julia.
Julia Bootcamp
by Cameron Pfiffer
Julia programming introduction.
Quantitative Editing: A Guide
by Laura Bronner
Data journalism practices.