explaingit

ossu/data-science

Analysis updated 2026-05-18

21,155Audience · vibe coderComplexity · 2/5Setup · easy

TLDR

Free, self-taught Data Science curriculum covering math, programming, databases, statistics, and machine learning through university courses and MOOCs.

Mindmap

mindmap
  root((repo))
    What it does
      Curated course list
      Progress tracking
      Two-year roadmap
    Topic areas
      Math foundations
      Programming basics
      Databases
      Statistics
      Machine learning
    Learning resources
      MIT OpenCourseWare
      Coursera courses
      edX courses
    Support
      Discord community
      Progress spreadsheet
      Fork and track
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Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Build a self-paced Data Science education plan without paying for bootcamps or university tuition.

USE CASE 2

Track your progress through a structured curriculum by forking the repo and checking off completed courses.

USE CASE 3

Learn foundational math, programming, and statistics needed for machine learning and data analysis roles.

USE CASE 4

Join a community of self-taught learners for support and accountability while working through the curriculum.

What is it built with?

PythonR

How does it compare?

ossu/data-sciencerasahq/rasaandroid/nowinandroid
Stars21,15521,15321,151
LanguagePythonKotlin
Setup difficultyeasyhardmoderate
Complexity2/54/53/5
Audiencevibe coderdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
License could not be detected automatically. Check the repository's LICENSE file before use.

In plain English

The Open Source Society University Data Science repository is a curated study path that walks you through the equivalent of an undergraduate data-science degree for free, using open courses from well-known universities and online platforms. It is not software you install or run, it is a structured reading list. The maintainers gather the best Massive Open Online Courses they can find, order them, and present the result as a curriculum you can follow on your own time. The structure follows the kind of progression a real degree would: an introduction to data science, an introduction to computer science and programming, then data structures and algorithms, databases, single-variable, linear-algebra and multivariable calculus, statistics and probability, data-science tools and methods, machine learning and data mining, and finally a project. The README explains how to use it: you can finish in about two years studying roughly twenty hours a week, you fork the repository on GitHub and tick items off as you go to track your progress, and a spreadsheet is provided so you can estimate your end date based on your own pace. The curriculum recommends that students already have high-school math and basic statistics before starting, and notes that Python and R are the two main programming languages used along the way, with Java introduced for the algorithms section. The project follows a published report titled "Curriculum Guidelines for Undergraduate Programs in Data Science" as its guide for choosing courses. Someone would use this if they want a serious self-taught path into data science without paying for a degree, and prefer a roadmap to chasing random tutorials. There is a Discord server and GitHub issues for talking with other learners.

Copy-paste prompts

Prompt 1
I want to learn Data Science from scratch. What's the best order to take these free courses: intro to CS, Python, linear algebra, statistics, databases, and machine learning?
Prompt 2
Help me create a study schedule for the OSSU Data Science curriculum assuming I have 20 hours per week available.
Prompt 3
What are the key prerequisites I need to master before starting the machine learning section of this curriculum?
Prompt 4
I'm using the OSSU Data Science repo to self-teach. How should I structure my own fork to track which courses I've completed?

Frequently asked questions

What is data-science?

Free, self-taught Data Science curriculum covering math, programming, databases, statistics, and machine learning through university courses and MOOCs.

What license does data-science use?

License could not be detected automatically. Check the repository's LICENSE file before use.

How hard is data-science to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is data-science for?

Mainly vibe coder.

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