This is a **solid path** for you that want to graduate in a Computer Science course in your own time, **for free**, with courses from the **best universities** of the World.
Here we will <strike>try to</strike> choose a maximum of **3** courses for each category. Futurely, more categories and/or courses can be added to this list or in a more advanced list.
Initially, we will also give preference for MOOC (Massive Open Online Course) type of courses because those courses were created with our style of learning in mind.
Making a [public commitment](http://renewablewealth.com/articles/the-power-of-a-public-commitment/), we have much more chances to **succeed** in our graduation, know better our fellows and share the things that we have done.
[Introduction to Computer Science](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#!)| 9 ~ 15 weeks
[Introduction to Computer Science and Programming Using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-5#!)| 9 weeks
[Introduction to Computational Thinking and Data Science](https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-2#!)| 10 weeks
[Effective Thinking Through Mathematics](https://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01x)| 9 weeks
[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
[Applications of Linear Algebra Part 2](https://www.edx.org/course/applications-linear-algebra-part-2-davidsonx-d003x-2)| 4 weeks
[Linear and Discrete Optimization](https://www.coursera.org/course/linearopt)| 3-6 hours/week
[Operating System Engineering](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-828-operating-system-engineering-fall-2012/)| -
[Operating Systems and System Programming](https://www.youtube.com/watch?v=XgQo4JkN4Bw&list=PL3289DD0D0F0CD4A3)| -
This guide was developed to be consumed in a linear approach. What this means? That you should do one course at a time.
The courses already **are** in the order that you should consume them. Just start in the **Introduction** section and after finishing the first course, start the next one.
**If the course isn't open, do it anyway with the resources from the previous class.**
### Should I take all courses?
**Yes**! The intention is to conclude **all** the courses listed here!
### Duration of the project
Maybe to finish all the classes we will spend **more time** than with a regular CS course, but I can **guarantee** to you that your **reward** will be proportional to **your motivation/dedication**!
### How can I track my progress?
You should create a repository on GitHub to put all files that you created for each course.
You can create one repository for each course, or just one repository that will contain all files for all courses. The first option is our preferred approach.
### Cooperative work
**We love cooperative work**! But is quite difficult manage a large base of students with specific projects. Use our channels to communicate with other fellows and to combine and create new projects.
### Which programming languages should I use?
My friend here is the awesome part of the liberty! You can use **any** language that you want to complete the courses.
The **important** thing for each course is to **internalize** the **core concepts** and be able to use them with whatever tool (programming language) that you touch.
### Stay tuned
[Watch](https://help.github.com/articles/watching-repositories/) this repository for futures improvements and general information.
- [Adding our university page at Linkedin](https://help.linkedin.com/app/answers/detail/a_id/40128/~/adding-a-new-university-page), so in that way we will be able to add **OSS University** in our Linkedin profile.
