Boniverski Computer Science Save
🎓 Path to a free self-taught education in Computer Science!
Open Source Society University
Path to a free self-taught education in Computer Science!
Contents
- About
- Motivation & Preparation
- Curriculum
- How to use this guide
- Prerequisite
- How to collaborate
- Community
- Team
- 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 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?
Curriculum
- Introduction to Computer Science
- Math (Mathematical Thinking)
- Program Design
- Math (Calculus & Discrete Math)
- Algorithms
- Programming Paradigms
- Software Testing
- Math (Calculus)
- Software Architecture
- Theory
- Software Engineering
- Math (Probability)
- Computer Architecture
- Operating Systems
- Computer Networks
- Databases
- Cloud Computing
- Math (Linear Algebra)
- Cryptography
- Security
- Compilers
- Parallel Computing
- UX Design
- Computer Graphics
- Artificial Intelligence
- Machine Learning
- Natural Language Processing
- Big Data
- Data Mining
- Internet of Things
- Specializations
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 |
Algorithms
| 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 |
Theory
| 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 |
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 |
Math (Linear Algebra)
| Courses | Duration | Effort |
|---|---|---|
| Linear Algebra - Foundations to Frontiers | 15 weeks | 8 hours/week |
Cryptography
| Courses | Duration | Effort |
|---|---|---|
| Cryptography I | 6 weeks | 5-7 hours/week |
| Cryptography II | 6 weeks | 6-8 hours/week |
Security
| Courses | Duration | Effort |
|---|---|---|
| Introduction to Cyber Security | 8 weeks | 3 hours/week |
Compilers
| 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 |
Specializations
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
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
- Create an account in Trello.
- 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 theSectionlabel 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!
- Markdown:
[](https://github.com/open-source-society/computer-science) - HTML:
<a href="https://github.com/open-source-society/computer-science"><img alt="Open Source Society University - Computer Science" src="https://img.shields.io/badge/OSSU-computer--science-blue.svg"></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.
Prerequisite
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
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:
Community
Subscribe to /r/opensourcesociety!
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 subreddit/group for important discussions.
Team
- Curriculum Founder: Eric Douglas
- Curriculum Maintainer: Eric Douglas
- Contributors: contributors
References
Open Source Agenda Badge
