The computer-science from faizalpribadi

Open Source Society University

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

About
Becoming an OSS student
Motivation & Preparation
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 our curriculum, we gave 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.

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.

MIT Challenge

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

Learning How to Learn

Are you ready to get started?

Curriculum

Introduction to Computer Science
Math (Mathematical Thinking)
Program Design
Math (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	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
From Nand to Tetris	7 weeks	5-10 hours/week

Math (Mathematical Thinking)

Courses	Duration	Effort
Effective Thinking Through Mathematics	9 weeks	5 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

Math (Discrete Math)

Courses	Duration	Effort
Mathematics for Computer Science	-	-

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
Functional Programming Principles in Scala	7 weeks	5-7 hours/week
Principles of Reactive Programming	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 One	16 weeks	8-10 hours/week
Calculus Two: Sequences and Series	7 weeks	9-10 hours/week
Multivariable Calculus	6 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

Theory

Courses	Duration	Effort
Automata	6 weeks	8-10 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
Startup Engineering	12 weeks	2-20 hours/week

Math (Probability)

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

Computer Architecture

Courses	Duration	Effort
The Hardware/Software Interface	8 weeks	10-15 hours/week
Computer Architecture	-	5-8 hours/week

Operating Systems

Courses	Duration	Effort
Operating System Engineering	-	-
Operating Systems and System Programming	10 weeks	-

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

Math (Linear Algebra)

Courses	Duration	Effort
Coding the Matrix: Linear Algebra through Computer Science Applications	10 weeks	7-10 hours/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

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
Heterogeneous Parallel Programming	11 weeks	8-10 hours/week

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	-

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

Specializations

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

Search such specializations in the following platforms:

Coursera | edX | Udacity | Future Learn | Udemy

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.

Project Based

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 "startup project".

"What does it mean?"

After finish a course, you should think about a real 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 informations in that file after you conclude it.

You can create this project alone or with other students!

Some project suggestions here and here.

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! 😄

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!

Change Log

Curriculum Version: 1.1.0

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.

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

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.

Next Goals

Add our University page at Linkedin, so in that way we will be able to add OSS University in our Linkedin profile.

faizalpribadi / computer-science Goto Github PK

computer-science's Introduction