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.

Learning How to Efficiently Learn

Before jumping into technical content, it’s crucial to build learning skills that will help you master complex subjects efficiently. This course offers science-backed strategies on memory, focus, and time management that will benefit you throughout the entire degree and beyond.

If it has been a while since you've been in the classroom or need to take your learning skills to the next level, this course is essential. It's a survival kit for those with busy lives who want to maximize efficiency while learning.

Courses	School	Duration	Effort	Frequency	Prerequisites
Learning How to Learn: Powerful mental tools to help you master tough subjects	Deep Teaching Solutions	4 weeks	4-5 hours/week	Self-paced	None

Computer Science Basics

This foundational section introduces core principles of computer science: how computers work, what programming is, and how to think algorithmically. It sets the stage for deeper technical learning.

Courses	School	Duration	Effort	Frequency	Prerequisites
CS50's Introduction to Computer Science	Harvard	12 weeks	10-20 hours/week	Self-paced	None

Programming

Programming is the language of computers. These courses teach you how to write, debug, and structure code using Python—an accessible yet powerful language widely used in industry.

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	6 weeks	4-6 hours/week	Self-paced	Programming for Everybody
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

Math is the backbone of computer science and data analysis. This section covers calculus, linear algebra, and statistics—tools that enable deeper understanding in AI, simulations, data science, and graphics.

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
Calculus 1C: Coordinate Systems & Infinite Series	MIT	8 weeks	6-10 hours/week	Self-paced	Calculus 1B
Linear Algebra - Foundations to Frontiers	UT Austin	15 weeks	6-10 hours/week	Self-paced	Pre-calculus
Introduction to Probability and Data with R	Duke University	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

This track introduces you to working with data: cleaning it, visualizing trends, and applying machine learning. Data science skills are in high demand across nearly every industry today.

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

Systems

Understanding systems gives insight into how computers work under the hood—from logic gates to operating systems. This knowledge helps you write more efficient, low-level code and grasp how software interacts with hardware.

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: Nand to Tetris Part II	Hebrew University of Jerusalem	6 weeks	10-15 hours/week	Once a month	Part I
Introduction to Operating Systems	Georgia Tech	8 weeks	5-8 hours/week	Self-paced	Nand to Tetris II

Theory

Theory teaches you how to solve problems efficiently and how to reason about algorithms and computation. It sharpens your ability to write code that not only works but works well.

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

Applications

Here, you explore how software applies in real-world domains like databases and cybersecurity. You’ll gain practical skills to manage and secure data, which are essential in industry roles.

Courses	School	Duration	Effort	Frequency	Prerequisites
Database Management Essentials	University of Colorado	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, Probability

Unix

The Unix command line is a powerful tool for developers. You’ll learn how to navigate systems, manage files, and automate workflows—skills critical for any software engineer or data scientist.

Courses	School	Duration	Effort	Frequency	Prerequisites
Linux Command Line Basics	Udacity	1 week	5 hours/week	Self-paced	None
The Unix Workbench	Johns Hopkins University	4 weeks	4 hours/week	Once a month	None

Networking

Computer networking is the foundation of how devices communicate and share information. This section helps you understand internet protocols, TCP/IP, DNS, HTTP, and real-world tools used in network administration.

Courses	School	Duration	Effort	Frequency	Prerequisites
Computer Networking: Principles, Protocols and Practice	UCLouvain	Self-paced	~20 hours	Self-paced	None
The Bits and Bytes of Computer Networking	Google	6 weeks	5 hours/week	Self-paced	None
Introduction to Networking	Cisco	4 weeks	4-6 hours/week	Self-paced	None
Network Security & Database Vulnerabilities	Rochester Institute of Technology	8 weeks	8-10 hours/week	Self-paced	Intro to networking

Software Engineering

This section focuses on professional software practices: how to write clean, maintainable code and work in teams using tools like Git and Agile methodology. You’ll also learn design patterns and testing techniques that lead to robust software systems.

Courses	School	Duration	Effort	Frequency	Prerequisites
Object-Oriented Programming in Java	Duke University	4 weeks	4-6 hours/week	Self-paced	Basic programming
Software Development Processes and Methodologies	University of Minnesota	4 weeks	4-6 hours/week	Self-paced	None
Agile with Atlassian Jira	Atlassian	4 weeks	4-5 hours/week	Self-paced	None
Design Patterns	University of Alberta	4 weeks	4-6 hours/week	Self-paced	OOP experience
Version Control with Git	Atlassian	4 weeks	2-4 hours/week	Self-paced	None
Test-Driven Development (TDD) in Python	Udemy	~3 hours	Self-paced	Python basics

This section helps you understand how to write maintainable, scalable, and testable code using modern software development methodologies and OOP principles. It also gives hands-on experience with tools like Git and Jira, used in real-world software teams.

Cybersecurity

Cybersecurity is the practice of protecting systems, networks, and programs from digital attacks. This section introduces you to fundamental security concepts, cryptography, and practical skills needed to defend and assess systems.

Courses	School	Duration	Effort	Frequency	Prerequisites
Introduction to Cyber Security Specialization	NYU (via Coursera)	~4 months	4-6 hours/week	Self-paced	None
Cybersecurity for Everyone	University of Maryland	8 weeks	4-6 hours/week	Self-paced	None
Cybersecurity Basics	IBM	6 hours	Self-paced	Self-paced	None
Introduction to Information Security	Udacity	6 weeks	6-8 hours/week	Self-paced	Basic computer skills

Specializations

After building core computer science skills, you can branch into specialized domains based on your interests or career goals. These specializations allow you to go deeper into high-impact fields such as web development, robotics, DevOps, blockchain, game development, and mobile apps.

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🌐 Web Development

Web development enables you to build interactive applications and deploy them on the internet. You’ll learn both the frontend (user interface) and backend (server logic), making you a well-rounded developer.

Courses	School	Duration	Effort	Frequency	Prerequisites
HTML, CSS, and Javascript for Web Developers	Johns Hopkins University	6 weeks	5-10 hours/week	Self-paced	None
Responsive Web Design	freeCodeCamp	~300 hours	Self-paced	Self-paced	None
JavaScript Algorithms and Data Structures	freeCodeCamp	~300 hours	Self-paced	Self-paced	None
Full Stack Open	University of Helsinki	~12 weeks	15-20 hours/week	Self-paced	Basic JS

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🤖 Robotics / Embedded Systems

This specialization explores how software controls hardware. You’ll gain hands-on experience with physical devices, sensors, and automation. It’s perfect for aspiring engineers interested in robotics, IoT, or embedded programming.

Courses	School	Duration	Effort	Frequency	Prerequisites
Introduction to Robotics	Columbia University	10 weeks	5-8 hours/week	Self-paced	Calculus, Linear Algebra
An Introduction to Programming the Internet of Things (IoT)	UC Irvine	6 months	6 hours/week	Self-paced	Python basics
Microcontrollers and the C Programming Language	University of Colorado	6 weeks	6-8 hours/week	Self-paced	C programming helpful
Build Your Own Internet of Things (IoT) System	Curtin University	6 weeks	3-4 hours/week	Self-paced	None

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☁️ DevOps & Cloud Engineering

DevOps bridges software development and IT operations, enabling faster delivery, scalable applications, and automation. Learn how to build CI/CD pipelines, manage infrastructure as code, and deploy in the cloud.

Courses	School	Duration	Effort	Frequency	Prerequisites
Google IT Automation with Python	Google	6 months	5-10 hours/week	Self-paced	Python
AWS Cloud Technical Essentials	AWS	4 weeks	3-5 hours/week	Self-paced	None
Introduction to DevOps	LinuxFoundationX	7 weeks	2-3 hours/week	Self-paced	None
Continuous Integration and Continuous Deployment (CI/CD)	IBM	4 weeks	4-5 hours/week	Self-paced	Intro to DevOps

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⛓️ Blockchain & Web3

Blockchain technology powers cryptocurrencies, decentralized applications (dApps), and smart contracts. This specialization introduces core blockchain concepts and gives hands-on experience with Ethereum, Solidity, and decentralized systems.

Courses	School	Duration	Effort	Frequency	Prerequisites
Blockchain Basics	University at Buffalo	4 weeks	4-6 hours/week	Self-paced	None
Ethereum and Solidity: The Complete Developer's Guide	Udemy	~24 hours	Self-paced	JavaScript helpful
Blockchain Specialization	University at Buffalo	~4 months	5-7 hours/week	Self-paced	Programming experience
CryptoZombies	Loom Network	Self-paced	~20 hours	Self-paced	None (interactive Solidity intro)

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🎮 Game Development

Game development combines creativity, mathematics, and performance optimization. Learn to build interactive 2D/3D games, implement game physics, and develop with engines like Unity or Godot.

Courses	School	Duration	Effort	Frequency	Prerequisites
Game Development for Beginners with Unity	Udemy	~20 hours	Self-paced	Self-paced	None
CS50’s Introduction to Game Development	Harvard	12 weeks	6-12 hours/week	Self-paced	Python or basic programming
Godot 4 Game Development for Beginners	Udemy	~15 hours	Self-paced	None
Mathematics for Computer Graphics	University of Tokyo	5 weeks	6-8 hours/week	Self-paced	Linear algebra

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📱 Mobile App Development

Mobile development lets you create apps for Android and iOS platforms. This track covers both native and cross-platform approaches, using tools like Kotlin, Swift, and Flutter.

Courses	School	Duration	Effort	Frequency	Prerequisites
Developing Android Apps with Kotlin	Google	~8 weeks	6-8 hours/week	Self-paced	Basic programming
iOS App Development with Swift	Stanford	~10 weeks	~8-10 hours/week	Self-paced	Programming experience
Flutter Development Bootcamp	Udemy	~30 hours	Self-paced	None
Multiplatform Mobile App Development with Web Technologies	Hong Kong University	5 weeks	6-8 hours/week	Self-paced	Web development basics

Capstone Project Suggestions

Capstone projects help you consolidate your knowledge by building something real. They also strengthen your portfolio, demonstrating your capabilities to potential employers or collaborators.

These projects allow you to apply your knowledge from across the curriculum in a real-world setting. Choose one or more depending on your interests:

1. Personal Portfolio Website

   • Stack: HTML, CSS, JavaScript, and optionally a JS framework (React/Vue)
   • Host it on GitHub Pages or Netlify
   • Include your resume and links to all your completed projects

2. Data Analysis Pipeline

   • Stack: Python, Pandas, Matplotlib/Seaborn, Jupyter
   • Choose a real dataset (e.g., from Kaggle) and perform EDA, visualizations, and modeling
   • Document everything in a clear report or Jupyter Notebook

3. Full-Stack Web App

   • Stack: React + Node.js/Express + MongoDB or PostgreSQL
   • Idea: Budget tracker, Task manager, Recipe app, etc.
   • Deploy using Vercel/Render and include authentication

4. Nand to Tetris Final Project

   • Complete the Nand2Tetris computer by building an assembler or operating system components
   • Demonstrate understanding of how computers work from the ground up

5. Machine Learning Mini Project

   • Stack: Python, scikit-learn, NumPy, Jupyter
   • Implement a classifier or predictor (e.g., spam detector, price predictor)
   • Explain your results and choices clearly

6. Open Source Contribution

   • Find a beginner-friendly issue on GitHub (tag: good first issue)
   • Fork, contribute, and document your process
   • Link the pull request in your portfolio