This is a **solid path** for those of you who want to complete a Computer Science course on your own time, **for free**, with courses from the **best universities** in the World.
Initially, we will also give preference to MOOC (Massive Open Online Course) type of courses because those courses were created with our style of learning in mind.
To officially register for this course you must create a profile in our [students profile](https://github.com/open-source-society/computer-science-and-engineering/issues/109) issue.
Comment in [this](https://github.com/open-source-society/computer-science-and-engineering/issues/109) issue (please, do **not** open a new one) using the following template:
By making a [public commitment](http://renewablewealth.com/articles/the-power-of-a-public-commitment/), we have a greater chance of **successfully** graduating, a way to get to know our peers better, and an opportunity to share the things that we have done.
[Introduction to Computer Science](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#!)| 12 weeks | 10-20 hours/week
[Introduction to Computer Science and Programming Using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-5#!)| 9 weeks | 15 hours/week
[Introduction to Computational Thinking and Data Science](https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-2#!)| 10 weeks | 15 hours/week
[Systematic Program Design- Part 1: The Core Method](https://www.edx.org/course/systematic-program-design-part-1-core-ubcx-spd1x-0)| 5 weeks | 8-12 hours/week
[Systematic Program Design- Part 2: Arbitrary Sized Data](https://www.edx.org/course/systematic-program-design-part-2-ubcx-spd2x)| 5 weeks | 8-12 hours/week
[Systematic Program Design- Part 3: Abstraction, Search and Graphs](https://www.edx.org/course/systematic-program-design-part-3-ubcx-spd3x)| 5 weeks | 8-12 hours/week
[Effective Thinking Through Mathematics](https://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01x)| 9 weeks | 5 hours/week
[Applications of Linear Algebra Part 1](https://www.edx.org/course/applications-linear-algebra-part-1-davidsonx-d003x-1#ct-read-review-widget)| 5 weeks | 12-18 hours/week
[Applications of Linear Algebra Part 2](https://www.edx.org/course/applications-linear-algebra-part-2-davidsonx-d003x-2)| 4 weeks | 12-18 hours/week
[Linear and Discrete Optimization](https://www.coursera.org/course/linearopt)| 7 weeks | 3-6 hours/week
[Engineering Software as a Service (SaaS), Part 1](https://www.edx.org/course/engineering-software-service-saas-part-1-uc-berkeleyx-cs169-1x)| 9 weeks | 12 hours/week
[Engineering Software as a Service (Saas), Part 2](https://www.edx.org/course/engineering-software-service-saas-part-2-uc-berkeleyx-cs169-2x)| 8 weeks | 12 hours/week
[Software Processes and Agile Practices](https://www.coursera.org/learn/software-processes-and-agile-practices)| 4 weeks | 6-8 hours/week
The courses are **already** in the order that you should complete them. Just start in the **Introduction** section and after finishing the first course, start the next one.
It may take longer to complete all of the classes compared to a regular CS course, but I can **guarantee** you that your **reward** will be proportional to **your motivation/dedication**!
You must focus on your **habit**, and **forget** about goals. Try to invest 1 ~ 2 hours **every day** studying this curriculum. If you do this, **inevitably** you'll finish this curriculum.
> See more about "Commit to a process, not a goal" [here](http://jamesclear.com/goals-systems).
You can create one repository per course, or just one repository that will contain all of the files for each course. The first option is our preferred approach.
**ps**: You should share **only** files that you are **allowed** to! **Do NOT disrespect the code of conduct** that you signed in the beginning of some courses.
**We love cooperative work**! But is quite difficult to manage a large base of students with specific projects. Use our channels to communicate with other fellows to combine and create new projects.
The **important** thing for each course is to **internalize** the **core concepts** and to be able to use them with whatever tool (programming language) that you wish.
This is a **crucial** part of your journey through all those courses.
You **need** to have in mind that what you are able to **create** with the concepts that you learned will be your certificate. **And this is what really matters**!
In order to show that you **really** learned those things, you need to be **creative**!
Here are some tips about how you can do that:
- **Articles**: create blog posts to synthesize/summarize what you learned.
- **GitHub repository**: keep your course's files organized in a GH repository, so in that way other students can use it to study with your annotations.
- **Real projects**: you can try to develop at least **one real project** for each course that you enroll. It doesn't need to be a big project, just a **small one** to **validate** and **consolidate** your knowledge. Some project suggestions [here](https://github.com/karan/Projects) and [here](https://github.com/ericdouglas/app-specs).
You can [open an issue](https://help.github.com/articles/creating-an-issue/) and give us your suggestions as to how we can improve this guide, or what we can do to improve the learning experience.
We also have a chat room! [](https://gitter.im/open-source-society/computer-science-and-engineering?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
> **ps**: A forum is an ideal way to interact with other students as we do not lose important discussions, which usually occur in communication via chat apps. **Please use our forum for important discussions**.
- [Adding our university page at Linkedin](https://help.linkedin.com/app/answers/detail/a_id/40128/~/adding-a-new-university-page), so that way we will be able to add **OSS University** in our Linkedin profile.
