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:mortar_board: Path to a free self-taught graduation in Computer Science

License: MIT License

computer-science's Introduction

open source society university

Open Source Society University

๐ŸŽ“ Path to a free self-taught graduation in Computer Science!

Contents

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

Courses
Introduction to Computer Science
Introduction to Computer Science and Programming Using Python
Introduction to Computational Thinking and Data Science

Program Design

Courses
Systematic Program Design- Part 1: The Core Method
Systematic Program Design- Part 2: Arbitrary Sized Data
Systematic Program Design- Part 3: Abstraction, Search and Graphs

Algorithms

Courses
Algorithms, Part I
Algorithms, Part II
Analysis of Algorithms

Programming Paradigms

Courses
Introduction to Functional Programming
Object Oriented Programming in Java
Principles of Reactive Programming
Programming Languages
Functional Programming Principles in Scala

Software Testing

Courses
Software Testing
Software Debugging

Math

Courses
Effective Thinking Through Mathematics
Applications of Linear Algebra Part 1
Applications of Linear Algebra Part 2
Linear and Discrete Optimization
Probabilistic Graphical Models
Game Theory

Software Architecture

Courses
Web Application Architectures
Software Architecture & Design
Microservice Architectures TODO

Software Engineering

Courses
Engineering Software as a Service (SaaS), Part 1
Engineering Software as a Service (Saas), Part 2
Software Product Management Specialization

Operating Systems

Courses
Operating System Engineering
Operating Systems and System Programming

Computer Networks

Courses
Computer Networks
Software Defined Networking

Databases

Courses
Introduction to Databases
Database Design
Database Management Essentials

Cloud Computing

Courses
Introduction to Cloud Computing
Cloud Computing Specialization

Cryptography

Courses
Cryptography I
Cryptography II
Applied Cryptography

Compilers

Courses
Compilers

UX Design

Courses
Interaction Design Specialization
UX Design for Mobile Developers

Artificial Intelligence

Courses
Artificial Intelligence

Machine Learning

Courses
Practical Machine Learning
Machine Learning
Neural Networks for Machine Learning

Natural Language Processing

Courses
Natural Language Processing
Natural Language Processing

Big Data

Courses
Big Data Specialization

Data Mining

Courses
Data Mining specialization

Internet of Things

Courses
The Internet of Things

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 here, adding 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! ๐Ÿ˜„

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! Join the chat at https://gitter.im/open-source-society/computer-science-and-engineering

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

References

computer-science's People

Contributors

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