Path to a free self-taught education in Computer Science!
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.
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:
Duration. It is possible to finish within about 2 years if you plan carefully and devote roughly 20 hours/week to your studies. Learners can use this spreadsheet to estimate their end date. Make a copy and input your start date and expected hours per week in the
Timeline sheet. As you work through courses you can enter your actual course completion dates in the
Curriculum Data sheet and get updated completion estimates.
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.
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!
Getting help (Details about our FAQ and chatroom)
8.0.0 (see CHANGELOG)
If you've never written a for-loop, or don't know what a string is in programming, start here. This course is self-paced, allowing you to adjust the number of hours you spend per week to meet your needs.
simple data structures
|Python for Everybody||10 weeks||10 hours/week||none||chat|
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!
basic data structures and algorithms
|Introduction to Computer Science and Programming using Python (alt)||9 weeks||15 hours/week||high school algebra||chat|
All coursework under Core CS is required, unless otherwise indicated.
design for testing
common design patterns
ML-family languages (via Standard ML)
Lisp-family languages (via Racket)
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.
|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|
Students must choose one of the following topics: calculus, linear algebra, logic, or probability.
|Calculus 1A: Differentiation||13 weeks||6-10 hours/week||high school math||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|
|Essence of Linear Algebra||-||-||high school math||chat|
|Linear Algebra||14 weeks||12 hours/week||Essence of Linear Algebra||chat|
|Introduction to Logic||10 weeks||4-8 hours/week||set theory||chat|
|Probability||24 weeks||12 hours/week||Differentiation and Integration||chat|
In addition to their math elective, students must complete the following course on discrete mathematics.
|Mathematics for Computer Science (alt)||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|
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.
terminals and shell scripting
command line environments
|The Missing Semester of Your CS Education||2 weeks||12 hours/week||-||chat|
manual memory management
|Courses||Duration||Effort||Additional Text / Assignments||Prerequisites||Discussion|
|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|
|Operating Systems: Three Easy Pieces||10-12 weeks||6-10 hours/week||-||algorithms, familiarity with C is useful||chat|
|Introduction to Computer Networking||8 weeks||4–12 hours/week||
|algebra, probability, basic CS||chat|
divide and conquer
sorting and searching
minimum spanning trees
|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|
Confidentiality, Integrity, Availability
Threats and Attacks
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.
|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
|Databases: Modeling and Theory||2 weeks||10 hours/week||core programming||chat|
|Databases: Relational Databases and SQL||2 weeks||10 hours/week||core programming||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|
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.
debugging theory and practice
object-oriented analysis and design
large-scale software architecture and design
|Parallel Programming||4 weeks||6-8 hours/week||Scala programming|
|Compilers||9 weeks||6-8 hours/week||none|
|Introduction to Haskell||14 weeks||-||-|
|Learn Prolog Now! (alt)*||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|
finite state machines
processor instruction sets
system call interface
|Computation Structures 1: Digital Circuits||10 weeks||6 hours/week||Nand2Tetris II|
|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|
distributed shared memory
state machine replication
computational geometry theory
|Theory of Computation (Lectures)||8 weeks||10 hours/week||discrete mathematics, logic, algorithms|
|Computational Geometry||16 weeks||8 hours/week||algorithms, C++|
|Game Theory||8 weeks||3 hours/week||mathematical thinking, probability, calculus|
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.
|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 with Unity 2020 (Specialization)||6 months||5 hours/week||programming, interactive design|
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!
[![Open Source Society University - Computer Science](https://img.shields.io/badge/OSSU-computer--science-blue.svg)](https://github.com/ossu/computer-science)
<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>
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.
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!
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.
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:
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
Sectionlabel 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.