Data Science for Beginners vs Python Data Science Handbook
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A free 10-week, 20-lesson beginner data science curriculum from Microsoft, with quizzes and assignments.
Open source · MIT
The full text of a Python data science book, delivered as runnable Jupyter notebooks.
The short answer
Choose Data Science for Beginners if you need…
- Complete beginners who want a guided, week-by-week data science course
- Students looking for free structured coursework
- Learners who prefer hands-on, project-based lessons over videos
- People who want to work through material in English or one of the many listed translations
Choose Python Data Science Handbook if you need…
- Students learning NumPy, Pandas, Matplotlib, or Scikit-Learn through hands-on examples
- Analysts who already know Python and want a practical tour of data science libraries
- Readers who prefer running code next to the text rather than only reading
- People who want to try the notebooks without local setup, using Colab or Binder
Side-by-side
| Data Science for Beginners | Python Data Science Handbook | |
|---|---|---|
| Type | Learning resource | Learning resource |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 37.9k | 50.3k |
| Setup difficulty | Beginner | Beginner |
| How you get it | Clone and build from source | Clone and build from source |
| Main language | Jupyter Notebook | Jupyter Notebook |
| Last code update | 16 days ago | 2 years ago |
What each one is
Data Science for Beginners
This is a structured course in data science for people who are new to the field. It is organized as 20 lessons spread over 10 weeks, and each lesson includes pre- and post-lesson quizzes, written instructions, a solution, and an assignment. The course uses a project-based approach, so you learn by building things.
Python Data Science Handbook
This repository holds the complete Python Data Science Handbook as Jupyter notebooks, so the explanations and the code examples live together. It introduces core Python data libraries such as IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. You can read it online, or run the notebooks yourself to try the code.
Best for
Data Science for Beginners
- Complete beginners who want a guided, week-by-week data science course
- Students looking for free structured coursework
- Learners who prefer hands-on, project-based lessons over videos
- People who want to work through material in English or one of the many listed translations
Python Data Science Handbook
- Students learning NumPy, Pandas, Matplotlib, or Scikit-Learn through hands-on examples
- Analysts who already know Python and want a practical tour of data science libraries
- Readers who prefer running code next to the text rather than only reading
- People who want to try the notebooks without local setup, using Colab or Binder
Strengths
Data Science for Beginners
- Free and MIT-licensed, so it can be reused and adapted
- Each lesson pairs instruction with quizzes and assignments
- Available in a large number of languages through the listed translations
Python Data Science Handbook
- Text and runnable code are combined in the same notebooks
- Free to read online, with Colab and Binder links for running code
- Code is released under the MIT license
Not ideal for
Data Science for Beginners
- Experienced data scientists looking for advanced techniques, since the README describes it as a beginner curriculum
- People who need a live instructor or cohort, since the README only describes self-paced written lessons and community channels
- Anyone expecting a software product to install, since this is a set of lesson materials
Python Data Science Handbook
- Complete beginners to Python: the README says familiarity with Python is assumed, and points to a separate companion project for that
- Readers who need current library versions: the book was tested with Python 3.5, and the README warns some pinned package versions may not be available on every platform
Trade-offs
Data Science for Beginners
- The README gives little detail on prerequisites or the exact topics covered in each lesson
- The full repository is large because of the many translations, though sparse checkout is offered to reduce download size
Python Data Science Handbook
- Written and tested with Python 3.5; newer library versions may behave differently, and the README admits some pinned versions may be unavailable
- The text is licensed CC-BY-NC-ND, which limits reuse and modification of the book content, unlike the MIT-licensed code
Getting started
Data Science for Beginners
Clone without translations (Bash / macOS / Linux)
git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.gitEnter the folder and set sparse checkout (Bash / macOS / Linux)
cd Data-Science-For-Beginners && git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'Python Data Science Handbook
Install requirements into the current conda environment
conda install --file requirements.txtCreate a stand-alone environment named PDSH with Python 3.5
conda create -n PDSH python=3.5 --file requirements.txtFrequently asked questions
What is the difference between Data Science for Beginners and Python Data Science Handbook?
Data Science for Beginners: A free 10-week, 20-lesson beginner data science curriculum from Microsoft, with quizzes and assignments. Python Data Science Handbook: The full text of a Python data science book, delivered as runnable Jupyter notebooks. Data Science for Beginners suits complete beginners who want a guided, week-by-week data science course, while Python Data Science Handbook suits students learning numpy, pandas, matplotlib, or scikit-learn through hands-on examples.
Are Data Science for Beginners and Python Data Science Handbook free?
Data Science for Beginners: Free and open source. Python Data Science Handbook: Free and open source.
Is Data Science for Beginners or Python Data Science Handbook more popular?
Python Data Science Handbook has more GitHub stars (50.3k) than Data Science for Beginners (37.9k). Popularity isn't the same as fit — check which one matches your use case above.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.