Boniverski Computer Science Save

🎓 Path to a free self-taught education in Computer Science!

Project README

Open Source Society University (OSSU)

Open Source Society University

Path to a free self-taught education in Computer Science!

Awesome Open Source Society University - Computer Science



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.

In our curriculum, we give preference to MOOC (Massive Open Online Course) style courses because these courses were created with our style of learning in mind.

Motivation & Preparation

Here are two interesting links that can make all the difference in your journey.

The first one is a motivational video that shows a guy that went through the "MIT Challenge", which consists of learning the entire 4-year MIT curriculum for Computer Science in 1 year.

The second link is a MOOC that will teach you learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. These are fundamental abilities to succeed in our journey.

Are you ready to get started?


Introduction to Computer Science

Courses Duration Effort
Introduction to Computer Science - CS50 12 weeks 10-20 hours/week

Math (Mathematical Thinking)

Courses Duration Effort
Effective Thinking Through Mathematics 4 weeks 2-5 hours/week

Program Design

Courses Duration Effort
How to Code: Systematic Program Design - Part 1 5 weeks 8-12 hours/week
How to Code: Systematic Program Design - Part 2 5 weeks 8-12 hours/week
How to Code: Systematic Program Design - Part 3 5 weeks 8-12 hours/week

Math (Calculus and Discrete Math)

Courses Duration Effort
Calculus One 16 weeks 8-10 hours/week
Mathematics for Computer Science 12 weeks 5 hours/week


Courses Duration Effort
Algorithms, Part I 6 weeks 6-12 hours/week
Algorithms, Part II 6 weeks 6-12 hours/week

Programming Paradigms

Courses Duration Effort
Functional Programming Principles in Scala 7 weeks 5-7 hours/week
Object Oriented Programming in Java 6 weeks 4-6 hours/week

Software Testing

Courses Duration Effort
Software Testing 4 weeks 6 hours/week
Software Debugging 8 weeks 6 hours/week

Math (Calculus)

Courses Duration Effort
Calculus Two: Sequences and Series 7 weeks 9-10 hours/week

Software Architecture

Courses Duration Effort
Software Architecture & Design 8 weeks 6 hours/week


Courses Duration Effort
Intro to Theoretical Computer Science 9 weeks 6 hours/week

Software Engineering

Courses Duration Effort
Software Processes and Agile Practices 4 weeks 6-8 hours/week

Math (Probability)

Courses Duration Effort
Introduction to Probability - The Science of Uncertainty 16 weeks 12 hours/week

Computer Architecture

Courses Duration Effort
Computer Architecture - 5-8 hours/week

Operating Systems

Courses Duration Effort
Operating Systems and System Programming 10 weeks 2-3 hours/week

Computer Networks

Courses Duration Effort
Computer Networks - 4–12 hours/week


Courses Duration Effort
Databases 12 weeks 8-12 hours/week

Cloud Computing

Courses Duration Effort
Introduction to Cloud Computing 4 weeks 1 hour/week

Math (Linear Algebra)

Courses Duration Effort
Linear Algebra - Foundations to Frontiers 15 weeks 8 hours/week


Courses Duration Effort
Cryptography I 6 weeks 5-7 hours/week
Cryptography II 6 weeks 6-8 hours/week


Courses Duration Effort
Introduction to Cyber Security 8 weeks 3 hours/week


Courses Duration Effort
Compilers 9 weeks 6-8 hours/week

Parallel Computing

Courses Duration Effort
Parallel Computer Architecture and Programming 20 weeks -

UX Design

Courses Duration Effort
UX Design for Mobile Developers 6 weeks 6 hours/week

Computer Graphics

Courses Duration Effort
Computer Graphics 6 weeks 12 hours/week

Artificial Intelligence

Courses Duration Effort
Artificial Intelligence 12 weeks 15 hours/week

Machine Learning

Courses Duration Effort
Machine Learning 11 weeks 4-6 hours/week

Natural Language Processing

Courses Duration Effort
Introduction to Natural Language Processing 12 weeks -

Big Data

Courses Duration Effort
Introduction to Big Data 3 weeks 5-6 hours/week

Data Mining

Courses Duration Effort
Pattern Discovery in Data Mining 4 weeks 4-6 hours/week

Internet of Things

Courses Duration Effort
The Internet of Things 4 weeks 2 hours/week


After finishing the courses above, start your specializations on the topics that you have more interest.

The following platforms currently offer specializations:

edX: xSeries

Coursera: Specializations

Udacity: Nanodegree

FutureLearn: Collections

keep learning

How to use this guide

Order of the classes

This guide was developed to be consumed in a linear approach. What does this mean? That you should complete one course at a time.

The courses are already in the order you should complete them. Just start in the Introduction to Computer Science section and after finishing the first course, start the next one.

OBS: If the course is not open, do it with the archived resources or wait until next class is open.

How to track and show your progress

  1. Create an account in Trello.
  2. Copy this board to your personal account. See how to copy a board here.

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 Courses: cards with that label represent courses that was 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 Section label are only to help the organization of the Done column. You should put the Course's cards below its respective Section's card.
  • Extra Sections: cards with that label represent sections that was added by the student.

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.

Should I take all courses?

Yes! The intention is to conclude all the courses listed here!

Duration of the project

It may take longer to complete all courses compared to a regular CS graduation, but I can guarantee you that your reward will be proportional to your extra effort!

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.

Project Based

Here in OSS University, you do not need to take exams, because we are focused on real projects!

In order to show everyone that you successfully finished a course, you should create a real project.

"What does it mean?"

After you finish a course, you should think about a real world problem that you can solve using the acquired knowledge in the course. You don't need to create a big project, but you must create something to validate and consolidate your knowledge, and also to show to the world that you are capable to create something useful with the concepts that you learned.

The projects of all students will be listed in this file. Submit your project's information in that file after you conclude it.

Put the OSSU-CS badge in the README of your repository! Open Source Society University - Computer Science

  • Markdown: [![Open Source Society University - Computer Science](](
  • HTML: <a href=""><img alt="Open Source Society University - Computer Science" src=""></a>

You can create this project alone or with other students!

Project Suggestions

  • Projects: A list of practical projects that anyone can solve in any programming language.
  • app-specs: A curated list of applications specifications and implementations to practice new technologies, improve your portfolio and sharpen your skills.
  • FreeCodeCamp: Course that teaches you fullstack JavaScript development through a bunch of projects.
  • JavaScript Projects: List of projects related with the JavaScript Path.

And you should also...

Be creative!

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.

Cooperative work

We love cooperative work! Use our channels to communicate with other fellows to combine and create new projects!

Which programming languages should I use?

My friend, here is the best part of 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 to be able to use them with whatever tool (programming language) that you wish.

Content Policy

You must share only files that you are allowed to! Do NOT disrespect the code of conduct that you signed in the beginning of some courses.

Be creative in order to show your progress! :smile:

Stay tuned

Watch this repository for futures improvements and general information.


The only things that you need to know are how to use Git and GitHub. Here are some resources to learn about them:

Note: Just pick one of the courses below to learn the basics. You will learn a lot more once you get started!

Change Log

Curriculum Version: 6.0

To show respect to all of our students, we will keep a CHANGELOG file that contains all the alterations that our curriculum may suffer.

Now we have a stable version of the curriculum, which won't change anymore, only in exceptional cases (outdated courses, broken links, etc).

Our students can trust in this curriculum because it has been carefully planned and covers all the core topics that a conventional Computer Science course covers.

We also include modern topics, making this course one of the best options for those who want to become a Computer Scientist and/or a Software Engineer/Developer.

How to collaborate

You can open 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.

You can also fork this project and send a pull request to fix any mistakes that you have found.

If you want to suggest a new resource, send a pull request adding such resource to the extras section.

The extras section is a place where all of us will be able to submit interesting additional articles, books, courses and specializations, keeping our curriculum as immutable and concise as possible.

Let's do it together! :smile:


Subscribe to /r/opensourcesociety!

Join us in our group!

You can also interact through GitHub issues.

We also have a chat room! Join the chat at

Add Open Source Society University to your Facebook profile!

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 subreddit/group for important discussions.



Open Source Agenda is not affiliated with "Boniverski Computer Science" Project. README Source: boniverski/computer-science
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