Looking for high-quality books to learn programming, data science, or AI — completely free? This post is a living catalog of trusted, open-access books covering:
- ✅ R and Shiny
- 🐍 Python
- 💡 Julia
- 📊 Statistics
- 🤖 Data Science & Machine Learning
📘 R Programming & Visualization
| Book Title | Author(s) | Link |
|---|
| R course | Berry Boessenkool | Link |
| R Markdown: The Definitive Guide | Yihui Xie et al. | Link |
| Mastering Shiny | Hadley Wickham | Link |
| Learning Shiny | Peter Baumgartner | Link |
| Unleash Shiny | David Granjon et al. | Link |
| R for Data Science (2e) | Wickham, Çetinkaya-Rundel | Link |
| Advanced R | Hadley Wickham | Link |
| Efficient R Programming | Gillespie, Lovelace | Link |
| Geocomputation with R | Lovelace et al. | Link |
| R Cookbook | Paul Teetor | Link |
| R Graphics Cookbook, 2nd edition | Winston Chang | Link |
| R Markdown Cookbook | Yihui Xie et al | Link |
| R Bootcamp | Yun Dai | Link |
| Learning Plotly | Peter Baumgartner | Link |
| blogdown: Creating Websites with R Markdown | Yihui Xie et al | Link |
| R for Non-Programmers | Daniel Dauber | Link |
🛠️ Books for R Package Development
| Book Title | Author(s) | Link |
|---|
| R Packages (2nd Ed) | Hadley Wickham, Jenny Bryan | Link |
| Happy Git with R | Jenny Bryan et al. | Link |
| The CRAN Cookbook | Jasmine Daly and Beni Altmann | Link |
🐍 Python Programming
| Book Title | Author(s) | Link |
|---|
| Python Data Science Handbook | Jake VanderPlas | Link |
| Automate the Boring Stuff with Python | Al Sweigart | Link |
| Dive Into Python 3 | Mark Pilgrim | Link |
| Think Python | Allen B. Downey | Link |
| FastAI Book | Jeremy Howard, Sylvain Gugger | Link |
💡 Julia Programming
| Book Title | Author(s) | Link |
|---|
| Think Julia | Ben Lauwens, Allen B. Downey | Link |
| Introduction to Computational Thinking | MIT / C. Rackauckas | Link |
| Statistics with Julia | Hayden Klok and Yoni Nazarathy | Link |
| Julia Data Science | Jose Storopoli aet al | Link |
📊 Statistics
| Book Title | Author(s) | Link |
|---|
| Statistical Rethinking (R Version) | Richard McElreath (Kurz) | Link |
| Introduction to Statistics | Lauren Perry | Link |
| OpenIntro Statistics | Diez, Barr, Çetinkaya-Rundel | Link |
| Practical Regression and Anova using R | Julian Faraway | Link |
| Applied regression analysis | Fabio M. Correa | Link |
| Introduction to Regression Methods for Public Health Using R | Ramzi W. Nahhas | Link |
| Geocomputation with R | Robin Lovelace et al | Link |
| Doing Bayesian Data Analysis in brms and the tidyverse | Solomon Kurz | Link |
| Statistical Tools for Causal Inference | Sylvain Chabé-Ferret | Link |
| Introduction to Bio-Medical data analysis with R | Nhan Thi Ho MD | Link |
| Advanced Statistical Modelling | S. Jackson | Link |
| Introductory Statistics for Economics | Brian Krauth | Link |
| Introduction to Bayesian Data Modeling | Andrés Ramírez-Hassan | Link |
| Sampling and Survey Techniques | Bakti Siregar | Link |
| Introduction to Bayesian Inference and Statistical Learning | University of Goettingen | Link |
🤖 Data Science & Machine Learning
| Book Title | Author(s) | Link |
|---|
| The Elements of Statistical Learning | Hastie, Tibshirani, Friedman | Link |
| Introduction to Statistical Learning (ISLR) | James, Witten, Hastie, Tibshirani | Link |
| Deep Learning Book | Ian Goodfellow et al. | Link |
| Pattern Recognition and Machine Learning | Christopher Bishop | Link |
| A Guide on Data Analysis | Mike Nguyen | Link |
| Doing Meta-Analysis in R: A Hands-on Guide | Mathias Harrer et al. | Link |
| Behavior Analysis with Machine Learning Using R | Enrique Garcia Ceja | link |
| Introductory predictive analytics and machine learning in education and healthcare | Anshul Kumar | Link |
| Introduction to Data Science | University of Konstanz | Link |
| Geographic Datascience with R | Peter Baumgartner | Link |
| Financial Data Science | Ryan Riordan | Link |
| Introduction to Environmental Data Science | Jerry Davis | Link |
| MetaNet: Network Analysis for Omics Data | Chen Peng | Link |
| Text Mining with R: A Tidy Approach | Julia Silge & David Robinson | Link |
| The Science of the Emotions | José Becerra | Link |
| Statistical Inference via Data Science | Chester Ismay and Albert Y. Kim | Link |
| Data Analysis with R | Joseph Fox | Link |
| Data Analysis and Visualization in R | Stefan Leach | Link |
| Data Science in Action | Kristopher Pruitt | Link |
Did I miss a great book? Feel free to suggest one!
Explore powerful books without spending a cent