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

Open Source Society University (OSSU)

Open Source Society University

Path to a self-taught education in Computer Science!

Awesome Open Source Society University - 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, at little to no cost, 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

Core CS

Core programming

Topics covered: imperative programming; procedural programming; C; basic data structures and algorithms; Python; SQL; HTML, CSS, JavaScript; basic testing; functional program composition; object-oriented program design; static typing; dynamic typing; common design patterns; ML-family languages (via Standard ML); Lisp-family languages (via Racket); Ruby; and more.

Courses Duration Effort Prerequisites
Introduction to Computer Science - CS50 12 weeks 10-20 hours/week none
How to Code: Systematic Program Design (XSeries) 15 weeks 5 hours/week none
Object Oriented Programming in Java 6 weeks 4-6 hours/week some programming
Programming Languages, Part A 4 weeks 8-16 hours/week recommended: Java, C
Programming Languages, Part B 3 weeks 8-16 hours/week Programming Languages, Part A
Programming Languages, Part C 3 weeks 8-16 hours/week Programming Languages, Part B

Note: The Object-Oriented Programming in Java class is intended for students who have already taken a basic Java course, but it can still be completed by those who have only studied basic programming before in a different, Java-like language (e.g., C). The learning curve will be steep, however, so for those who find it too difficult, looking over the material in this course is recommended: Introduction to Programming in Java.

Core math

Topics covered: mathematical proofs; number theory; real analysis; differential calculus; integral calculus; sequences and series; probability theory; basic statistics; O-notation; graph theory; linear transformations; matrices; vectors; and more.

Courses Duration Effort Prerequisites
Introduction to Mathematical Thinking 10 weeks 10 hours/week high school math
Calculus One 16 weeks 8-10 hours/week pre-calculus
Calculus Two: Sequences and Series 7 weeks 9-10 hours/week Calculus One
Introduction to Probability - The Science of Uncertainty 18 weeks 12 hours/week calculus
Discrete Mathematics 11 weeks 3-5 hours/week high school math
Linear Algebra - Foundations to Frontiers 15 weeks 8 hours/week high school math

Core systems

Topics covered: boolean algebra; gate logic; memory; machine language; computer architecture; assembly; machine language; virtual machines; high-level languages; compilers; operating systems; relational databases; transaction processing; data modeling; network protocols; and more.

Courses Duration Effort Prerequisites
Build a Modern Computer from First Principles: From Nand to Tetris 6 weeks 7-13 hours/week none
Build a Modern Computer from First Principles: Nand to Tetris Part II 6 weeks 12-18 hours/week Part I
Databases 12 weeks 8-12 hours/week some programming, basic CS
Introduction to Computer Networking - 4–12 hours/week algebra, probability, basic CS

Note 1: The 'From Nand to Tetris' course, in part I, will have you create an entire computer architecture from scratch, but are missing key elements from computer architecture such as pipelining and memory hierarchy. A supplemental textbook is recommended for those interested in the subject: Computer Organization and Design.

Note 2: Part II of the same course has you build the very lowest levels of an operating system on top of the computer architecture you built, however it does not go very deep into operating systems. For those interested in this subject, this free supplemental textbook is strongly recommended: Operating Systems: Three Easy Pieces.

Core theory

Topics covered: divide and conquer; sorting and searching; randomized algorithms; graph search; shortest paths; data structures; greedy algorithms; minimum spanning trees; dynamic programming; NP-completeness; formal languages; Turing machines; computability; and more.

Courses Duration Effort Prerequisites
Algorithms (1/4) 4 weeks 4-8 hours/week one programming language; proofs; probability
Algorithms (2/4) 4 weeks 4-8 hours/week previous algorithms course
Algorithms (3/4) 4 weeks 4-8 hours/week previous algorithms course
Algorithms (4/4) 4 weeks 4-8 hours/week previous algorithms course
Automata Theory 8 weeks 10 hours/week discrete mathematics

Core applications

Topics covered: neural networks; supervised learning; unsupervised learning; OpenGL; raytracing; block ciphers; authentication; public key encryption; and more.

Courses Duration Effort Prerequisites
Machine Learning 11 weeks 4-6 hours/week linear algebra
Computer Graphics 6 weeks 12 hours/week C++ or Java, linear algebra
Cryptography I 6 weeks 5-7 hours/week linear algebra; probability

Advanced programming

Topics covered: code coverage; random testing; debugging theory and practice; GPU programming; CUDA; parallel computing; object-oriented analysis and design; UML; large-scale software architecture and design; and more.

Courses Duration Effort Prerequisites
Software Testing 4 weeks 6 hours/week some programming
Software Debugging 8 weeks 6 hours/week Python, object-oriented programming
Introduction to Parallel Programming 12 weeks - C, algorithms
Software Architecture & Design 8 weeks 6 hours/week Java programming

Electives

Some of these courses are offered less frequently, but you are encouraged to take them whenever they are available if you're interested. Compilers is recommended to any student who took a strong interest in the Programming Languages courses. Natural Language Processing is recommended to anyone who thinks they want to specialize in machine learning, artificial intelligence, etc. Cryptography is recommended to anyone who wants to learn more about zero knowledge systems and other advanced topics in cryptography.

Courses Duration Effort Prerequisites
Cryptography II 6 weeks 6-8 hours/week Cryptography I
Compilers 9 weeks 6-8 hours/week none
Introduction to Natural Language Processing 12 weeks - Python programming

Pro CS

After finishing the curriculum above, you will have completed close to a full bachelor's degree in Computer Science. You can stop here, but if you really want to make yourself valuable, the next step to completing your studies is to develop skills and knowledge in a specific domain.

Choose one or more of the following specializations:

These aren't the only specializations you can choose. Check the following websites for more options:

edX: xSeries

Coursera: Specializations

Udacity: Nanodegree

FutureLearn: Collections

keep learning

How to use this guide

Order of the classes

This guide was developed to be flexible. Ideally, it can be consumed in a linear approach, i.e. you complete one course at a time, but in reality different people have different preferences with regard to how many courses they wish to take at once. Plus, different courses are available at different times and have wildly different time requirements.

Therefore, many students will take the courses in a non-linear order, based on availability and how much time they have to devote to each class.

Any course that is part of 'Core CS' section should be available either regularly, in self-paced format, or in archived form. Some of the electives are only available once in a while.

How to track and show your progress

  1. Create an account in Trello.
  2. 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 the Section label 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?

If you are serious about getting an online education comparable to a bachelor's degree in Computer Science, you should absolutely take all of the courses under the 'Core CS' section.

These courses are equivalent to about 3/4 of a full bachelor's degree in CS. So if you want to really complete your studies, then you should select one of the specializations to finish out your program, such as one in Artificial Intelligence or Big Data.

Duration of the project

If you are able to devote 18-20 hours per week to this curriculum, taking 1-3 clases at a time, you could hypothetically finish the Core CS section in under 2 years. A specialization would then take you a few more months.

It will probably take longer if you go slower, but regardless, your reward will be proportional to your 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

OSS University is project-focused. You are encouraged to do the assignments and exams for each course, but what really matters is whether you can use your knowledge to solve a real world problem.

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 problem that you can solve using the acquired knowledge in the course. It doesn't have to be a big project, but rather it should show the world that you are capable of creating something useful with the concepts that you learned.

It won't make sense to do a project for every course, as some have no immediate practical application. But anytime you gain practical skills (e.g., a new programming language), you should use it right away to validate and consolidate your knowledge.

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! Open Source Society University - Computer Science

  • Markdown: [![Open Source Society University - Computer Science](https://img.shields.io/badge/OSSU-computer--science-blue.svg)](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 project.

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

This curriculum assumes the student has already taken high school math, including algebra, geometry, and pre-calculus. Some high school students will have taken calculus, but this is usually only about 3/4 of a college calculus class, so the calculus courses listed above are still recommended.

Apart from those, 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 resources below to learn the basics. You will learn a lot more once you get started!

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 the major core topics that a conventional Computer Science program covers.

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! 😄

Community

Subscribe to /r/opensourcesociety!

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

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

References