**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.
- We have a chat room! This should be your first stop to talk with other OSSU students. Why don't you introduce yourself right now? [Join the chat in Gitter](https://gitter.im/open-source-society/computer-science) [](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. Read more [here](CONTRIBUTING.md).
- Add **Open Source Society University** to your [Linkedin](https://www.linkedin.com/school/11272443/) 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](./FAQ.md#why-is-the-firebase-ossu-app-different-or-broken).
- [Core CS](#core-cs) assumes the student has already taken [high school math](https://www.khanacademy.org/math/high-school-math), including algebra, geometry, and pre-calculus.
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
The How to Code courses are based on the textbook [How to Design Programs](https://htdp.org/2003-09-26/). The First Edition is available for free online and includes problem sets and solutions. Students are encouraged to do these assignments.
[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
[Introduction to Logic](https://www.coursera.org/learn/logic-introduction) | 10 weeks | 4-8 hours/week | set theory
#### Probability
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[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
[Mathematics for Computer Science](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-spring-2015/index.htm) | 13 weeks | 5 hours/week | An alternate version with solutions to the problem sets is [here](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2005/assignments/). Students struggling can consider the [Discrete Mathematics Specialization](https://www.coursera.org/specializations/discrete-mathematics) first. It is more interactive but less comprehensive, and costs money to unlock full interactivity. | Calculus 1C
[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
[Divide and Conquer, Sorting and Searching, and Randomized Algorithms](https://www.coursera.org/learn/algorithms-divide-conquer) | 4 weeks | 4-8 hours/week | any programming language, Mathematics for Computer Science
[Graph Search, Shortest Paths, and Data Structures](https://www.coursera.org/learn/algorithms-graphs-data-structures) | 4 weeks | 4-8 hours/week | Divide and Conquer, Sorting and Searching, and Randomized Algorithms
[Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming](https://www.coursera.org/learn/algorithms-greedy) | 4 weeks | 4-8 hours/week | Graph Search, Shortest Paths, and Data Structures
[Shortest Paths Revisited, NP-Complete Problems and What To Do About Them](https://www.coursera.org/learn/algorithms-npcomplete) | 4 weeks | 4-8 hours/week | Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
Note: **_These courses are provisionally recommended_**. There is an open [Request For Comment](https://github.com/ossu/computer-science/issues/639) on security course selection. Contributors are encouraged to compare the various courses in the RFC and offer feedback.
[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. Congratulations!
- 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.
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.
