Open Source Society University
Path to a free self-taught education in Computer Science!
- Becoming an OSS student
- Motivation & Preparation
- How to use this guide
- How to collaborate
- Next Goals
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 gave preference to MOOC (Massive Open Online Course) style courses because those courses were created with our style of learning in mind.
Becoming an OSS student
To officially register for this course you must create a profile in our web app .
"How can I do this?"
Just create an account on GitHub and log in with this account in our web app.
The intention of this app is to offer for 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.
In the "My Progress" tab, you are able to edit the status of the courses that you are taking, and also add the link of your final project for each one.
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", that consists in 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
- Math (Mathematical Thinking)
- Program Design
- Math (Discrete Math)
- Programming Paradigms
- Software Testing
- Math (Calculus)
- Software Architecture
- Software Engineering
- Math (Probability)
- Computer Architecture
- Operating Systems
- Computer Networks
- Cloud Computing
- Math (Linear Algebra)
- Parallel Computing
- UX Design
- Computer Graphics
- Artificial Intelligence
- Machine Learning
- Natural Language Processing
- Big Data
- Data Mining
- Internet of Things
Introduction to Computer Science
|Introduction to Computer Science – CS50||12 weeks||10-20 hours/week|
Math (Mathematical Thinking)
|Effective Thinking Through Mathematics||9 weeks||5 hours/week|
|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 (Discrete Math)
|Mathematics for Computer Science||12 weeks||5 hours/week|
|Algorithms, Part I||6 weeks||6-12 hours/week|
|Algorithms, Part II||6 weeks||6-12 hours/week|
|Functional Programming Principles in Scala||7 weeks||5-7 hours/week|
|Object Oriented Programming in Java||6 weeks||4-6 hours/week|
|Software Testing||4 weeks||6 hours/week|
|Software Debugging||8 weeks||6 hours/week|
|Calculus One||16 weeks||8-10 hours/week|
|Calculus Two: Sequences and Series||7 weeks||9-10 hours/week|
|Software Architecture & Design||8 weeks||6 hours/week|
|Automata||6 weeks||8-10 hours/week|
|Software Processes and Agile Practices||4 weeks||6-8 hours/week|
|Introduction to Probability – The Science of Uncertainty||16 weeks||12 hours/week|
|Computer Architecture||–||5-8 hours/week|
|Operating Systems and System Programming||10 weeks||2-3 hours/week|
|Computer Networks||–||4–12 hours/week|
|Databases||12 weeks||8-12 hours/week|
|Introduction to Cloud Computing||4 weeks||1 hour/week|
Math (Linear Algebra)
|Coding the Matrix: Linear Algebra through Computer Science Applications||10 weeks||7-10 hours/week|
|Cryptography I||6 weeks||5-7 hours/week|
|Cryptography II||6 weeks||6-8 hours/week|
|Introduction to Cyber Security||8 weeks||3 hours/week|
|Compilers||9 weeks||6-8 hours/week|
|Heterogeneous Parallel Programming||11 weeks||8-10 hours/week|
|UX Design for Mobile Developers||6 weeks||6 hours/week|
|Computer Graphics||6 weeks||12 hours/week|
|Artificial Intelligence||12 weeks||15 hours/week|
|Machine Learning||11 weeks||4-6 hours/week|
Natural Language Processing
|Natural Language Processing||10 weeks||8-10 hours/week|
|Introduction to Big Data||3 weeks||5-6 hours/week|
|Pattern Discovery in Data Mining||4 weeks||4-6 hours/week|
Internet of Things
|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:
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 that you should complete them. Just start in theIntroduction to Computer Sciencesection 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
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 .
Here in OSS University , you do not need to take exams, because we are focused on real projects !
In order to show for everyone that you successfully finished a course, you should create a real project .
"What does it mean?"
After 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 inthis file. Submit your project’s information in that file after you conclude it.
You can create this project alone or with other students!
- 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.
And you should also…
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.
We love cooperative work! Use ourchannelsto 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.
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 creativein order to show your progress!
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!
- Try Git
- Git – the simple guide
- GitHub Training & Guides
- GitHub Hello World
- Git Immersion
- How to Use Git and GitHub
To show respect to all of our students, we will keep aCHANGELOG 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.
How to collaborate
You canopen 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 alsofork this project and send apull 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 theextras 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! =)
Subscribe to /r/opensourcesociety !
Join us in our group !
You can also interact throughGitHub issues.
We also have a chat room!
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 .
- Add our University page at Linkedin , so in that way we will be able to add OSS University in our Linkedin profile.