Open Source Society University

Path to a free self-taught education in Computer Science!

Contents

• Summary
• Community
• Curriculum
• Code of conduct
• Team

Summary

The OSSU curriculum is a complete education in computer science using online materials. It's not merely for career training or professional development. It's for those who want a proper, well-rounded grounding in concepts fundamental to all computing disciplines, and for those who have the discipline, will, and (most importantly!) good habits to obtain this education largely on their own, but with support from a worldwide community of fellow learners.

It is designed according to the degree requirements of undergraduate computer science majors, minus general education (non-CS) requirements, as it is assumed most of the people following this curriculum are already educated outside the field of CS. The courses themselves are among the very best in the world, often coming from Harvard, Princeton, MIT, etc., but specifically chosen to meet the following criteria.

Courses must:

• Be open for enrollment
• Run regularly (ideally in self-paced format, otherwise running multiple times per year)
• Be of generally high quality in teaching materials and pedagogical principles
• Match the curricular standards of the CS 2013: Curriculum Guidelines for Undergraduate Degree Programs in Computer Science

When no course meets the above criteria, the coursework is supplemented with a book. When there are courses or books that don't fit into the curriculum but are otherwise of high quality, they belong in extras/courses or extras/readings.

Organization. The curriculum is designed as follows:

• Intro CS: for students to try out CS and see if it's right for them
• Core CS: corresponds roughly to the first three years of a computer science curriculum, taking classes that all majors would be required to take
• Advanced CS: corresponds roughly to the final year of a computer science curriculum, taking electives according to the student's interests
• Final Project: a project for students to validate, consolidate, and display their knowledge, to be evaluated by their peers worldwide

Duration. It is possible to finish Core CS within about 2 years if you plan carefully and devote roughly 18-22 hours/week to your studies. Courses in Core CS should be taken linearly if possible, but since a perfectly linear progression is rarely possible, each class's prerequisites are specified so that you can design a logical but non-linear progression based on the class schedules and your own life plans.

Cost. All or nearly all course material is available for free. However, some courses may charge money for assignments/tests/projects to be graded. Note that Coursera offers financial aid.

Decide how much or how little to spend based on your own time and budget; just remember that you can't purchase success!

Process. Students can work through the curriculum alone or in groups, in order or out of order.

• For grouping up, please use the cohorts repository to find or create a cohort suited to you.
• We recommend doing all courses in Core CS, only skipping a course when you are certain that you've already learned the material previously.
• For simplicity, we recommend working through courses (especially Core CS) in order from top to bottom, as they have already been topologically sorted by their prerequisites.
• Courses in Advanced CS are electives. Choose one subject (e.g. Advanced programming) you want to become an expert in and take all the courses under that heading. You can also create your own custom subject, but we recommend getting validation from the community on the subject you choose.

Content policy. If you plan on showing off some of your coursework publicly, you must share only files that you are allowed to. Do NOT disrespect the code of conduct that you signed in the beginning of each course!

How to contribute

Getting help (Details about our FAQ and chatroom)

Community

• We have a discord server! This should be your first stop to talk with other OSSU students. Why don't you introduce yourself right now? Join the CS channel in OSSU Discord
• You can also interact through GitHub issues. If there is a problem with a course, or a change needs to be made to the curriculum, this is the place to start the conversation. Read more here.
• Add Open Source Society University to your Linkedin profile!
• Note: There is an unmaintained and deprecated firebase app that you might find when searching OSSU. You can safely ignore it. Read more in the FAQ.

Curriculum

Curriculum version: 8.0.0 (see CHANGELOG)

• Prerequisites
• Intro CS
  • Introduction to Programming
  • Introduction to Computer Science
  • Introduction to CS Tools
• Core CS
  • Core programming
  • Core math
  • Core systems
  • Core theory
  • Core applications
  • Core security
• Advanced CS
  • Advanced programming
  • Advanced systems
  • Advanced theory
  • Advanced applications
• Final project

---

Prerequisites

• Core CS assumes the student has already taken high school math, including algebra, geometry, and pre-calculus.
• Advanced CS assumes the student has already taken the entirety of Core CS and is knowledgeable enough now to decide which electives to take.
• Note that Advanced systems assumes the student has taken a basic physics course (e.g. AP Physics in high school).

Intro CS

Introduction to Programming

If you've never written a for-loop, or don't know what a string is in programming, start here.

Topics covered: simple programs simple data structures

Courses	Duration	Effort	Prerequisites	Discussion
Python for Everybody	34 weeks	3 hours/week	none	chat

Introduction to Computer Science

This course will introduce you to the world of computer science. Students who have been introduced to programming, either from the courses above or through study elsewhere, should take this course for a flavor of the material to come. If you finish the course wanting more, Computer Science is likely for you!

Topics covered: computation imperative programming basic data structures and algorithms and more

Courses	Duration	Effort	Prerequisites	Discussion
Introduction to Computer Science and Programming using Python (alt)	9 weeks	15 hours/week	high school algebra	chat

Introduction to CS Tools

Understanding theory is important, but you will also be expected to create programs. There are a number of tools that are widely used to make that process easier. Learn them now to ease your future work writing programs.

Topics covered: terminals and shell scripting vim command line environments version control and more

Courses	Duration	Effort	Prerequisites	Discussion
The Missing Semester of Your CS Education	2 weeks	12 hours/week	-	chat

Core CS

All coursework under Core CS is required, unless otherwise indicated.

Core programming

Topics covered: functional programming design for testing program requirements common design patterns unit testing object-oriented design Java static typing dynamic typing ML-family languages (via Standard ML) Lisp-family languages (via Racket) Ruby and more

The How to Code courses are based on the textbook How to Design Programs. The First Edition is available for free online and includes problem sets and solutions. Students are encouraged to do these assignments.

Courses	Duration	Effort	Prerequisites	Discussion
How to Code - Simple Data	7 weeks	8-10 hours/week	none	chat
How to Code - Complex Data	6 weeks	8-10 hours/week	How to Code: Simple Data	chat
Programming Languages, Part A	5 weeks	4-8 hours/week	How to Code (Hear instructor)	chat
Programming Languages, Part B	3 weeks	4-8 hours/week	Programming Languages, Part A	chat
Programming Languages, Part C	3 weeks	4-8 hours/week	Programming Languages, Part B	chat

Math Electives

Students must choose one of the following topics: calculus, linear algebra, logic, or probability.

Calculus

Courses	Duration	Effort	Prerequisites	Discussion
Calculus 1A: Differentiation	13 weeks	6-10 hours/week	pre-calculus	chat
Calculus 1B: Integration	13 weeks	5-10 hours/week	Calculus 1A	chat
Calculus 1C: Coordinate Systems & Infinite Series	6 weeks	5-10 hours/week	Calculus 1B	chat

Linear Algebra

Courses	Duration	Effort	Prerequisites	Discussion
Essence of Linear Algebra	-	-	pre-calculus	chat
Linear Algebra	14 weeks	12 hours/week	Essence of Linear Algebra	chat

Logic

Courses	Duration	Effort	Prerequisites	Discussion
Introduction to Logic	10 weeks	4-8 hours/week	set theory	chat

Probability

Courses	Duration	Effort	Prerequisites	Discussion
Probability	24 weeks	12 hours/week	Multivariable Calculus	chat

Core Math

In addition to their math elective, students must complete the following course on discrete mathematics.

Topics covered: discrete mathematics mathematical proofs basic statistics O-notation discrete probability and more

Courses	Duration	Effort	Notes	Prerequisites
Mathematics for Computer Science	13 weeks	5 hours/week	An alternate version with solutions to the problem sets is here. Students struggling can consider the Discrete Mathematics Specialization first. It is more interactive but less comprehensive, and costs money to unlock full interactivity.	Calculus 1C	chat

Core systems

Topics covered: procedural programming manual memory management boolean algebra gate logic memory computer architecture assembly machine language virtual machines high-level languages compilers operating systems network protocols and more

Courses	Duration	Effort	Additional Text / Assignments	Prerequisites
Introduction to Computer Science - CS50 (alt)	12 weeks	10-20 hours/week	After the sections on C, skip to the next course. Why?	introductory programming	chat
Build a Modern Computer from First Principles: From Nand to Tetris (alt)	6 weeks	7-13 hours/week	-	C-like programming language	chat
Build a Modern Computer from First Principles: Nand to Tetris Part II	6 weeks	12-18 hours/week	-	one of these programming languages, From Nand to Tetris Part I	chat
Introduction to Computer Networking	8 weeks	4–12 hours/week	Assignment 1 Assignment 2 Assignment 3 Assignment 4	algebra, probability, basic CS	chat
Operating Systems: Three Easy Pieces	10-12 weeks	6 hours/week	-	algorithms	chat

Core theory

Topics covered: divide and conquer sorting and searching randomized algorithms graph search shortest paths data structures greedy algorithms minimum spanning trees dynamic programming NP-completeness and more

Courses	Duration	Effort	Prerequisites	Discussion
Divide and Conquer, Sorting and Searching, and Randomized Algorithms	4 weeks	4-8 hours/week	any programming language, Mathematics for Computer Science	chat
Graph Search, Shortest Paths, and Data Structures	4 weeks	4-8 hours/week	Divide and Conquer, Sorting and Searching, and Randomized Algorithms	chat
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming	4 weeks	4-8 hours/week	Graph Search, Shortest Paths, and Data Structures	chat
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them	4 weeks	4-8 hours/week	Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming	chat

Core Security

Topics covered Confidentiality, Integrity, Availability Secure Design Defensive Programming Threats and Attacks Network Security Cryptography and more

Note: These courses are provisionally recommended. There is an open Request For Comment on security course selection. Contributors are encouraged to compare the various courses in the RFC and offer feedback.

Courses	Duration	Effort	Prerequisites	Discussion
Information Security: Context and Introduction	5 weeks	3 hours/week	-	chat
Principles of Secure Coding	4 weeks	4 hours/week	-	chat
Identifying Security Vulnerabilities	4 weeks	4 hours/week	-	chat

Choose one of the following:

Courses	Duration	Effort	Prerequisites	Discussion
Identifying Security Vulnerabilities in C/C++Programming	4 weeks	5 hours/week	-	chat
Exploiting and Securing Vulnerabilities in Java Applications	4 weeks	5 hours/week	-	chat

Core applications

Topics covered: Agile methodology REST software specifications refactoring relational databases transaction processing data modeling neural networks supervised learning unsupervised learning OpenGL raytracing and more

Courses	Duration	Effort	Prerequisites	Discussion
Relational Databases and SQL	2 weeks	10 hours/week	core programming	chat
Databases: Modeling and Theory	2 weeks	10 hours/week	Relational Databases and SQL	chat
Databases: Semistructured Data	2 weeks	10 hours/week	core programming	chat
Machine Learning	11 weeks	4-6 hours/week	linear algebra	chat
Computer Graphics	6 weeks	12 hours/week	C++ or Java, linear algebra	chat
Software Engineering: Introduction	6 weeks	8-10 hours/week	Core Programming, and a sizable project	chat
Software Development Capstone Project	6-7 weeks	8-10 hours/week	Software Engineering: Introduction	chat

Advanced CS

After completing every required course in Core CS, students should choose a subset of courses from Advanced CS based on interest. Not every course from a subcategory needs to be taken. But students should take every course that is relevant to the field they intend to go into.

The Advanced CS study should then end with one of the Specializations under Advanced applications. A Specialization's Capstone, if taken, may act as the Final project, if permitted by the Honor Code of the course. If not, or if a student chooses not to take the Capstone, then a separate Final project will need to be done to complete this curriculum.

Advanced programming

Topics covered: debugging theory and practice goal-oriented programming GPU programming CUDA parallel computing object-oriented analysis and design UML large-scale software architecture and design and more

Courses	Duration	Effort	Prerequisites
Parallel Programming	4 weeks	6-8 hours/week	Scala programming
Compilers (alt)	9 weeks	6-8 hours/week	none
Introduction to Haskell	14 weeks	-	-
Learn Prolog Now!	12 weeks	-	-
Software Debugging	8 weeks	6 hours/week	Python, object-oriented programming
Software Testing	4 weeks	6 hours/week	Python, programming experience
Software Architecture & Design	8 weeks	6 hours/week	software engineering in Java

Advanced systems

Topics covered: digital signaling combinational logic CMOS technologies sequential logic finite state machines processor instruction sets caches pipelining virtualization parallel processing virtual memory synchronization primitives system call interface and more

Courses	Duration	Effort	Prerequisites
Electricity and Magnetism, Part 11	7 weeks	8-10 hours/week	calculus, basic mechanics
Electricity and Magnetism, Part 2	7 weeks	8-10 hours/week	Electricity and Magnetism, Part 1
Computation Structures 1: Digital Circuits	10 weeks	6 hours/week	electricity, magnetism
Computation Structures 2: Computer Architecture	10 weeks	6 hours/week	Computation Structures 1
Computation Structures 3: Computer Organization	10 weeks	6 hours/week	Computation Structures 2

¹ Note: These courses assume knowledge of basic physics. (Why?) If you are struggling, you can find a physics MOOC or utilize the materials from Khan Academy: Khan Academy - Physics

Advanced theory

Topics covered: formal languages Turing machines computability event-driven concurrency automata distributed shared memory consensus algorithms state machine replication computational geometry theory propositional logic relational logic Herbrand logic concept lattices game trees and more

Courses	Duration	Effort	Prerequisites
Theory of Computation (Lectures)	8 weeks	10 hours/week	discrete mathematics, logic, algorithms
Computational Geometry	16 weeks	8 hours/week	algorithms, C++
Introduction to Formal Concept Analysis	6 weeks	4-6 hours/week	logic, probability
Game Theory	8 weeks	3 hours/week	mathematical thinking, probability, calculus

Advanced applications

These Coursera Specializations all end with a Capstone project. Depending on the course, you may be able to utilize the Capstone as your Final Project for this Computer Science curriculum. Note that doing a Specialization with the Capstone at the end always costs money. So if you don't wish to spend money or use the Capstone as your Final, it may be possible to take the courses in the Specialization for free by manually searching for them, but not all allow this.

Courses	Duration	Effort	Prerequisites
Modern Robotics (Specialization)	26 weeks	2-5 hours/week	freshman-level physics, linear algebra, calculus, linear ordinary differential equations
Data Mining (Specialization)	30 weeks	2-5 hours/week	machine learning
Big Data (Specialization)	30 weeks	3-5 hours/week	none
Internet of Things (Specialization)	30 weeks	1-5 hours/week	strong programming
Cloud Computing (Specialization)	30 weeks	2-6 hours/week	C++ programming
Fullstack Open	12 weeks	6 hours/week	programming
Data Science (Specialization)	43 weeks	1-6 hours/week	none
Functional Programming in Scala (Specialization)	29 weeks	4-5 hours/week	One year programming experience
Game Design and Development (Specialization)	6 months	5 hours/week	programming, interactive design

Final project

OSS University is project-focused. You are encouraged to do the assignments and exams for each course, but what really matters is whether you can use your knowledge to solve a real-world problem.

After you've gotten through all of Core CS and the parts of Advanced CS relevant to you, you should think about a problem that you can solve using the knowledge you've acquired. Not only does real project work look great on a resume, but the project will also validate and consolidate your knowledge. You can create something entirely new, or you can find an existing project that needs help via websites like CodeTriage or First Timers Only.

Another option is using the Capstone project from taking one of the Specializations in Advanced applications; whether or not this makes sense depends on the course, the project, and whether or not the course's Honor Code permits you to display your work publicly. In some cases, it may not be permitted; do not violate your course's Honor Code!

Put the OSSU-CS badge in the README of your repository!

• Markdown: [![Open Source Society University - Computer Science](https://img.shields.io/badge/OSSU-computer--science-blue.svg)](https://github.com/ossu/computer-science)
• HTML: <a href="https://github.com/ossu/computer-science"><img alt="Open Source Society University - Computer Science" src="https://img.shields.io/badge/OSSU-computer--science-blue.svg"></a>

Evaluation

Upon completing your final project, submit your project's information to PROJECTS via a pull request and use our community channels to announce it to your fellow students.

Your peers and mentors from OSSU will then informally evaluate your project. You will not be "graded" in the traditional sense — everyone has their own measurements for what they consider a success. The purpose of the evaluation is to act as your first announcement to the world that you are a computer scientist and to get experience listening to feedback — both positive and negative — and taking it in stride.

The final project evaluation has a second purpose: to evaluate whether OSSU, through its community and curriculum, is successful in its mission to guide independent learners in obtaining a world-class computer science education.

Cooperative work

You can create this project alone or with other students! We love cooperative work! Use our channels to communicate with other fellows to combine and create new projects!

Which programming languages should I use?

My friend, here is the best part of liberty! You can use any language that you want to complete the final project.

The important thing is to internalize the core concepts and to be able to use them with whatever tool (programming language) that you wish.

Congratulations

After completing the requirements of the curriculum above, you will have completed the equivalent of a full bachelor's degree in Computer Science. Congratulations!

What is next for you? The possibilities are boundless and overlapping:

• Look for a job as a developer!
• Check out the readings for classic books you can read that will sharpen your skills and expand your knowledge.
• Join a local developer meetup (e.g. via meetup.com).
• Pay attention to emerging technologies in the world of software development:
  • Explore the actor model through Elixir, a new functional programming language for the web based on the battle-tested Erlang Virtual Machine!
  • Explore borrowing and lifetimes through Rust, a systems language which achieves memory- and thread-safety without a garbage collector!
  • Explore dependent type systems through Idris, a new Haskell-inspired language with unprecedented support for type-driven development.

Code of conduct

OSSU's code of conduct.

How to show your progress

1. Create an account in Trello.
2. Copy this board to your personal account. See how to copy a board here.

Now that you have a copy of our official board, you just need to pass the cards to the Doing column or Done column as you progress in your study.

We also have labels to help you have more control through the process. The meaning of each of these labels is:

• Main Curriculum: cards with that label represent courses that are listed in our curriculum.
• Extra Resources: cards with that label represent courses that were added by the student.
• Doing: cards with that label represent courses the student is current doing.
• Done: cards with that label represent courses finished by the student. Those cards should also have the link for at least one project/article built with the knowledge acquired in such course.
• Section: cards with that label represent the section that we have in our curriculum. Those cards with the Section label are only to help the organization of the Done column. You should put the Course's cards below its respective Section's card.

The intention of this board is to provide our students a way to track their progress, and also the ability to show their progress through a public page for friends, family, employers, etc. You can change the status of your board to be public or private.

Team

• Eric Douglas: founder of OSSU
• hanjiexi: lead technical maintainer
• waciumawanjohi: lead academic maintainer
• Contributors