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 at least once a month or so)
- Fulfill the [academic requirements](REQUIREMENTS.md) of OSSU
- Fit neatly into the progression of the curriculum with respect to topics and difficulty level
- Be of generally high quality in teaching materials and pedagogical principles
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](extras/courses.md) or [extras/readings](extras/readings.md).
**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
- *Pro CS*: graduate-level specializations students can elect to take after completing the above curriculum if they want to maximize their chances of getting a good job
**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,
**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](https://github.com/ossu/cohorts) 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](https://en.wikipedia.org/wiki/Topological_sorting) 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.
**Getting help**. Please check our [Frequently Asked Questions](FAQ.md), and if you cannot find the answer, file an issue or talk to our [friendly community](#community)!
- [Core CS](#core-cs) assumes the student has already taken high school math and physics, including algebra, geometry, and pre-calculus.
Some high school graduates will have already taken AP Calculus, but this is usually only about 3/4 of a college calculus class, so the calculus courses in the curriculum are still recommended.
- [Advanced CS](#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](#advanced-systems) assumes the student has taken a basic physics course (e.g. AP Physics in high school).
If you've never written a for-loop, or don't know what a string is in programming, start here. Choose one of the two course series below. Either one will give you an introduction to programming that assumes no prior knowledge.
Trying to decide between them?
_Python for Everyone_ will introduce you to a popular language and will quickly move to practical programming tasks - using web APIs and databases. This will give you a taste of what many professional developers do.
_Fundamentals of Computing_ will also start by introducing you to Python. It then moves on to give an introduction to academic Computer Science topics, like sorting and recursion. This will give you a taste of what the following courses will be like. (Students who complete _Fundamentals of Computing_ can skip Intro to Computer Science and begin Core CS.)
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!
[Introduction to Computer Science and Programming using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-10) ([alt](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/)) | 9 weeks | 15 hours/week | high school algebra
[How to Code - Complex Data](https://www.edx.org/course/how-code-complex-data-ubcx-htc2x) | 6 weeks | 8-10 hours/week | How to Code: Simple Data
[Software Construction - Data Abstraction](https://www.edx.org/course/software-construction-data-abstraction-ubcx-softconst1x) | 6 weeks | 8-10 hours/week | How to Code - Complex Data
[Software Construction - Object-Oriented Design](https://www.edx.org/course/software-construction-object-oriented-ubcx-softconst2x) | 6 weeks | 8-10 hours/week | Software Construction - Data Abstraction
[Programming Languages, Part A](https://www.coursera.org/learn/programming-languages) | 4 weeks | 8-16 hours/week | recommended: Java, C
[Programming Languages, Part B](https://www.coursera.org/learn/programming-languages-part-b) | 3 weeks | 8-16 hours/week | Programming Languages, Part A
[Programming Languages, Part C](https://www.coursera.org/learn/programming-languages-part-c) | 3 weeks | 8-16 hours/week | Programming Languages, Part B
<sup>**1**</sup>: Students struggling with MIT Math for CS can consider taking the [Discrete Mathematics Specialization](https://www.coursera.org/specializations/discrete-mathematics) first.
It is more interactive but less comprehensive, and it costs money to unlock full interactivity.
[Introduction to Computer Science - CS50](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#!) ([alt](https://cs50.harvard.edu/)) | 12 weeks | 10-20 hours/week | After the sections on C, skip to the next course. [Why?](FAQ.md#why-do-you-recommend-skipping-the-second-half-of-cs50) | introductory programming
[Build a Modern Computer from First Principles: From Nand to Tetris](https://www.coursera.org/learn/build-a-computer) ([alt](http://www.nand2tetris.org/)) | 6 weeks | 7-13 hours/week | - | C-like programming language
[Build a Modern Computer from First Principles: Nand to Tetris Part II ](https://www.coursera.org/learn/nand2tetris2) | 6 weeks | 12-18 hours/week | - | one of [these programming languages](https://user-images.githubusercontent.com/2046800/35426340-f6ce6358-026a-11e8-8bbb-4e95ac36b1d7.png), From Nand to Tetris Part I
[Introduction to Probability - The Science of Uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2) | 18 weeks | 12 hours/week | Multivariable Calculus
[Electricity and Magnetism, Part 2](https://www.edx.org/course/electricity-magnetism-part-2-ricex-phys102-2x-0) | 7 weeks | 8-10 hours/week | Electricity and Magnetism, Part 1
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.
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.
Another option is using the Capstone project from taking one of the Specializations in [Advanced applications](#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!
[](https://github.com/ossu/computer-science)
- Markdown: `[](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>`
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.
After completing the requirements of the curriculum above, you will have completed the equivalent of a full bachelor's degree in Computer Science, or quite close to one.
- Pay attention to emerging technologies in the world of software development:
+ Explore the **actor model** through [Elixir](http://elixir-lang.org/), a new functional programming language for the web based on the battle-tested Erlang Virtual Machine!
+ Explore **borrowing and lifetimes** through [Rust](https://www.rust-lang.org/), a systems language which achieves memory- and thread-safety without a garbage collector!
+ Explore **dependent type systems** through [Idris](https://www.idris-lang.org/), a new Haskell-inspired language with unprecedented support for type-driven development.
- We have a chat room! This should be your first stop to talk with other OSSU students. [](https://gitter.im/open-source-society/computer-science?utm_campaign=pr-badge&utm_content=badge&utm_medium=badge&utm_source=badge)
- You can also interact through [GitHub issues](https://github.com/ossu/computer-science/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.
- 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](./FAQ.md).
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.
