The Python Open Source Computer Science Degree

This is a curated list of free courses from reputable universities like MIT, Stanford, and Princeton that satisfy the same requirements as an undergraduate Computer Science degree, minus general education.

Computer Science Basics

Courses	School	Duration	Effort	Frequency	Prerequisites
Intro to Computer Science	Harvard	10 weeks	10-20 hours/week	self-paced	none

Programming

Courses	School	Duration	Effort	Frequency	Prerequisites
Programming for Everybody (Getting Started with Python)	University of Michigan	4 weeks	4-6 hours/week	self-paced	none
Python Data Structures	University of Michigan	4 weeks	4-6 hours/week	self-paced	Programming for Everybody (Getting Started with Python)
Using Python to Access Web Data	University of Michigan	4 weeks	4-6 hours/week	self-paced	Python Data Structures
Using Databases with Python	University of Michigan	3 weeks	4-8 hours/week	self-paced	Using Python to Access Web Data
Capstone: Retrieving, Processing, and Visualizing Data with Python	University of Michigan	2 weeks	4-6 hours/week	self-paced	Using Databases with Python

Alternative

Courses	School	Duration	Effort	Frequency	Prerequisites
Python 3 Programming Specialization	University of Michigan	5 months	7 hours/week	self-paced	none

Math

Courses	School	Duration	Effort	Frequency	Prerequisites
Calculus 1A: Differentiation	MIT	12 weeks	6-10 hours/week	self-paced	pre-calculus
Calculus 1B: Integration	MIT	15 weeks	6-10 hours/week	self-paced	Calculus 1A: Differentiation
Calculus 1C: Coordinate Systems & Infinite Series	MIT	8 weeks	6-10 hours/week	self-paced	Calculus 1B: Integration
Linear Algebra - Foundations to Frontiers	UT Austin	15 weeks	6-10 hours/week	self-paced	pre-calculus
Introduction to Probability and Data	Duke	5 weeks	5-7 hours/week	twice a month	none
Intro to Statistics	Udacity	8 weeks	5-7 hours/week	self-paced	none

Data Science

Courses	School	Duration	Effort	Frequency	Prerequisites
Introduction to Data Science in Python	University of Michigan	3 weeks	4-6 hours/week	self-paced	basic programming knowledge
Applied Plotting, Charting & Data Representation in Python	University of Michigan	4 weeks	5-7 hours/week	self-paced	Introduction to Data Science in Python
Applied Machine Learning in Python	University of Michigan	6 weeks	5-7 hours/week	self-paced	Applied Plotting, Charting & Data Representation in Python
Applied Text Mining in Python	University of Michigan	5 weeks	5-7 hours/week	self-paced	Applied Machine Learning in Python
Applied Social Network Analysis in Python	University of Michigan	5 weeks	5-7 hours/week	self-paced	Applied Text Mining in Python

Systems

Courses	School	Duration	Effort	Frequency	Prerequisites
Build a Modern Computer from First Principles: From Nand to Tetris	Hebrew University of Jerusalem	6 weeks	5 hours/week	twice a month	basic programming knowledge
Build a Modern Computer from First Principles: From Nand to Tetris II	Hebrew University of Jerusalem	6 weeks	10-15 hours/week	once a month	Build a Modern Computer from First Principles: From Nand to Tetris

Theory

Courses	School	Duration	Effort	Frequency	Prerequisites
Computer Science: Algorithms, Theory, and Machines	Princeton	10 weeks	2-5 hours/week	once a month	Calculus 1A (all), basic programming
Algorithms, Part I	Princeton	6 weeks	6-12 hours/week	once a month	Computer Science: Algorithms, Theory, and Machines
Algorithms, Part II	Princeton	6 weeks	6-12 hours/week	once a month	Algorithms, Part I

Applications

Courses	School	Duration	Effort	Frequency	Prerequisites
Database Management Essentials	CU	7 weeks	4-6 hours/week	twice a month	basic programming & CS knowledge
Cryptography I	Stanford	7 weeks	5 hours/week	once a month	Linear Algebra - Foundations to Frontiers & Introduction to Probability and Data

Unix

Courses	School	Duration	Effort	Frequency	Prerequisites
Linux Command Line Basics	IBM	1 week	12 hours/week	self-paced	none
The Unix Workbench	JHU	4 weeks	4 hours/week	once a month	none

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🚀 How to Use This Repository

This repository is designed as a self-learning roadmap for Computer Science using Python.

Steps to Follow:

1. Start with Programming Basics to understand Python fundamentals.
2. Move to Data Structures & Algorithms using Python.
3. Learn Databases, Operating Systems, and Computer Networks.
4. Practice by writing small Python programs for each topic.
5. Use this repository as a reference, not a replacement for practice.

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👨‍🎓 Who Is This Repository For?

This repository is helpful for:

• Beginners starting Python
• Computer Science students
• Self-learners without a CS background
• Students preparing for internships and placements

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🤝 How to Contribute

Contributions are welcome and appreciated.

You can contribute by:

• Improving documentation
• Fixing typos or formatting
• Adding learning resources
• Adding simple Python examples
• Suggesting better learning paths

Contribution Steps:

1. Fork this repository
2. Clone your fork
3. Make changes
4. Commit and push
5. Create a Pull Request

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🗺 Suggested Learning Path

A recommended order to follow:

1. Python Programming Basics
2. Data Structures using Python
3. Algorithms
4. Databases (SQL + Python)
5. Operating Systems
6. Computer Networks
7. System Design Basics

Consistency and practice matter more than speed.