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Open Source Society University
🎓 Path to a free self-taught graduation in Computer Science!
Contents
- About
- Becoming an OSS student
- Curriculum
- How to use this guide
- Prerequisite
- How to collaborate
- Community
- Next Goals
- References
About
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 the future, more categories and/or courses will be added to this list or a more advanced/specialized list.
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.
Becoming an OSS student
To officially register for this course you must create a profile in our students profile issue.
"How can I do this?"
Comment in this issue (please, do not open a new one) using the following template:
- **Name**: YOUR NAME
- **GitHub**: [@your_username]()
- **Twitter**: [@your_username]()
- **Linkedin**: [link]()
- **Website**: [yourblog.com]()
## Completed Courses
**Name of the Section**
Course|Files
:--|:--:
Course Name| [link]()
IMPORTANT: add your profile only once and after you finish each course you can return to that issue and update your comment.
ps: In the Completed Courses section, you should link the repository that contains the files that you created in the respective course.
"Why should I do this?"
By making 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.
That is why we are using this strategy.
Curriculum
- Introduction
- Program Design
- Algorithms
- Programming Paradigms
- Software Testing
- Math
- Software Architecture
- Software Engineering
- Operating Systems
- Computer Networks
- Databases
- Cloud Computing
- Cryptography
- Compilers
- UX Design
- Artificial Intelligence
- Machine Learning
- Natural Language Processing
- Big Data
- Data Mining
- Internet of Things
Introduction
| Courses | Duration | Effort |
|---|---|---|
| Introduction to Computer Science | 12 weeks | 10-20 hours/week |
| Introduction to Computer Science and Programming Using Python | 9 weeks | 15 hours/week |
| Introduction to Computational Thinking and Data Science | 10 weeks | 15 hours/week |
Program Design
| Courses | Duration | Effort |
|---|---|---|
| Systematic Program Design- Part 1: The Core Method | 5 weeks | 8-12 hours/week |
| Systematic Program Design- Part 2: Arbitrary Sized Data | 5 weeks | 8-12 hours/week |
| Systematic Program Design- Part 3: Abstraction, Search and Graphs | 5 weeks | 8-12 hours/week |
Algorithms
| Courses | Duration | Effort |
|---|---|---|
| Algorithms, Part I | 6 weeks | 6-12 hours/week |
| Algorithms, Part II | 6 weeks | 6-12 hours/week |
| Analysis of Algorithms | 6 weeks | 6-8 hours/week |
Programming Paradigms
| Courses | Duration | Effort |
|---|---|---|
| Introduction to Functional Programming | 7 weeks | 4-6 hours/week |
| Object Oriented Programming in Java | 6 weeks | 4-6 hours/week |
| Principles of Reactive Programming | 7 weeks | 5-7 hours/week |
| Functional Programming Principles in Scala | 7 weeks | 5-7 hours/week |
Software Testing
| Courses | Duration | Effort |
|---|---|---|
| Software Testing | 4 weeks | 6 hours/week |
| Software Debugging | 8 weeks | 6 hours/week |
Math
| Courses | Duration | Effort |
|---|---|---|
| Effective Thinking Through Mathematics | 9 weeks | 5 hours/week |
| Applications of Linear Algebra Part 1 | 5 weeks | 12-18 hours/week |
| Applications of Linear Algebra Part 2 | 4 weeks | 12-18 hours/week |
| Linear and Discrete Optimization | 7 weeks | 3-6 hours/week |
| Probabilistic Graphical Models | 11 weeks | 15-20 hours/week |
| Game Theory | 9 weeks | 5-7 hours/week |
Software Architecture
| Courses | Duration | Effort |
|---|---|---|
| Web Application Architectures | 6 weeks | 6-9 hours/week |
| Software Architecture & Design | 8 weeks | 6 hours/week |
Software Engineering
| Courses | Duration | Effort |
|---|---|---|
| Engineering Software as a Service (SaaS), Part 1 | 9 weeks | 12 hours/week |
| Engineering Software as a Service (Saas), Part 2 | 8 weeks | 12 hours/week |
| Software Processes and Agile Practices | 4 weeks | 6-8 hours/week |
Operating Systems
| Courses | Duration | Effort |
|---|---|---|
| Operating System Engineering | - | - |
| Operating Systems and System Programming | - | - |
Computer Networks
| Courses | Duration | Effort |
|---|---|---|
| Introduction to Computer Networking | - | 5-10 hours/week |
| Computer Networks | - | 4–12 hours/week |
Databases
| Courses | Duration | Effort |
|---|---|---|
| Databases | 12 weeks | 8-12 hours/week |
Cloud Computing
| Courses | Duration | Effort |
|---|---|---|
| Introduction to Cloud Computing | 4 weeks | 1 hour/week |
Cryptography
| Courses | Duration | Effort |
|---|---|---|
| Cryptography I | 6 weeks | 5-7 hours/week |
| Cryptography II | 6 weeks | 6-8 hours/week |
| Applied Cryptography | 8 weeks | 6 hours/week |
Compilers
| Courses | Duration | Effort |
|---|---|---|
| Compilers | 11 weeks | 8-10 hours/week |
UX Design
| Courses | Duration | Effort |
|---|---|---|
| UX Design for Mobile Developers | 6 weeks | 6 hours/week |
Artificial Intelligence
| Courses | Duration | Effort |
|---|---|---|
| Artificial Intelligence | 12 weeks | 15 hours/week |
Machine Learning
| Courses | Duration | Effort |
|---|---|---|
| Machine Learning | 11 weeks | - |
Natural Language Processing
| Courses | Duration | Effort |
|---|---|---|
| Natural Language Processing | 10 weeks | 8-10 hours/week |
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 |
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 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
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.
How can I track/show my progress?
To track your progress, you should update the profile that you created and add the courses that you began or ended.
To show your progress, you should create a repository on GitHub to put all of the files that you created for each course.
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.
Be creative in order to show your progress! 😄
Cooperative work
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.
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.
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.
- 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 and here.
Stay tuned
Watch this repository for futures improvements and general information.
Prerequisite
The only things that you need to know are how to use Git and GitHub. Here are some resources to learn about them:
ps: You don't need to do all of the courses. Just pick one and learn the basics because you will learn more on the go!
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 fix any mistakes that you have found.
Let's do it together! =)
Community
Join us in our group!
You can also interact through GitHub 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 forum for important discussions.
Next Goals
- Adding our university page at Linkedin, so that way we will be able to add OSS University in our Linkedin profile.