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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 curriculum 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; but we include readings where appropriate. The curriculum then concludes with a final project to show off your skills to your friends and future employers.

Motivation & Preparation

Here is an interesting link that can make all the difference in your journey. It's 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.

Are you ready to get started?

Curriculum

See also: Prerequisites

Intro CS

Use the first course, CS50, to determine if Computer Science is right for you. Only proceed in the curriculum if it really excites you. Feel free to use the second and third optional courses to gain the fundamental skills you need to excel at teaching yourself Computer Science; they are very lightweight courses so it's suggested take them concurrently with another course.

Topics covered: imperative programming; procedural programming; C; manual memory management; basic data structures and algorithms; basic Python; SQL; basic HTML, CSS, JavaScript; and more.

Courses Duration Effort Prerequisites
Introduction to Computer Science - CS50 12 weeks 10-20 hours/week none
Learning How to Learn 4 weeks 2 hours/week none
Effective Thinking Through Mathematics 4 weeks 2 hours/week none

Core CS

Core programming

Topics covered: functional programming; design for testing; program requirements; common design patterns; unit testing; object-oriented design; Java; static typing; dynamic typing; ML-family languages (via Standard ML); Lisp-family languages (via Racket); Ruby; and more.

Courses Duration Effort Prerequisites
How to Code - Simple Data 7 weeks 8-10 hours/week none
How to Code - Complex Data 6 weeks 8-10 hours/week How to Code: Simple Data
Software Construction - Data Abstraction 6 weeks 8-10 hours/week How to Code - Complex Data
Software Construction - Object-Oriented Design 6 weeks 8-10 hours/week Software Construction - Data Abstraction
Programming Languages (A, B, C) 10 weeks 8-16 hours/week recommended: C and Java

Readings

Core math

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

Courses Duration Effort Prerequisites
Linear Algebra - Foundations to Frontiers 15 weeks 8 hours/week pre-calculus
Calculus One 16 weeks 8-10 hours/week pre-calculus
Calculus Two: Sequences and Series 7 weeks 9-10 hours/week Calculus One
Mathematics for Computer Science 13 weeks 5 hours/week single variable calculus (Calculus Two)

Core systems

Topics covered: boolean algebra; gate logic; memory; machine language; computer architecture; assembly; machine language; virtual machines; high-level languages; compilers; operating systems; 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 From Nand to Tetris Part I
Introduction to Computer Networking - 4–12 hours/week algebra, probability, basic CS

Readings

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; 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 Algorithms (1/4)
Algorithms (3/4) 4 weeks 4-8 hours/week Algorithms (2/4)
Algorithms (4/4) 4 weeks 4-8 hours/week Algorithms (3/4)

Core applications

Topics covered: Agile methodology; REST; software specifications; refactoring; relational databases; transaction processing; data modeling; neural networks; supervised learning; unsupervised learning; OpenGL; raytracing; block ciphers; authentication; public key encryption; and more.

Courses Duration Effort Prerequisites
Databases 12 weeks 8-12 hours/week some programming, basic CS
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
Software Engineering: Introduction 6 weeks 8-10 hours/week Software Construction - Object-Oriented Design
Software Development Capstone Project1 6-7 weeks 8-10 hours/week Software Engineering: Introduction

1 Required if you intend not to go past Core CS; strongly recommended even for those who will continue on to Advanced CS.

Advanced CS

After completing every required course in Core CS, students should choose a subset of courses from Advanced CS based on interest. Not every course from a subcategory needs to be taken. But students should take every course that is relevant to the field they intend to go into.

The Advanced CS study should then end with one of the Specializations under Advanced applications. A Specialization's Capstone, if taken, may act as the Final project, if permitted by the Honor Code of the course. If not, or if a student chooses not to take the Capstone, then a separate Final project will need to be done to complete this curriculum.

Advanced programming

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

Courses Duration Effort Prerequisites
Compilers 9 weeks 6-8 hours/week none
Software Debugging 8 weeks 6 hours/week Python, object-oriented programming
LAFF: Programming for Correctness 7 weeks 6 hours/week linear algebra
Introduction to Parallel Programming 12 weeks - C, algorithms
Software Architecture & Design 8 weeks 6 hours/week software engineering in Java

Advanced math

Topics covered: real analysis; multivariable integrals; multivariable differentials; probability theory; and more.

Courses Duration Effort Prerequisites
Introduction to Mathematical Thinking 10 weeks 10 hours/week pre-calculus
Multivariable Calculus 13 weeks 12 hours/week single-variable calculus (Calculus Two)
Introduction to Probability - The Science of Uncertainty 18 weeks 12 hours/week single- and multi-variable calculus

Advanced systems

Topics covered: digital signaling; combinational logic; CMOS technologies; sequential logic; finite state machines; processor instruction sets; caches; pipelining; virtualization; parallel processing; virtual memory; synchronization primitives; system call interface; and more.

Courses Duration Effort Prerequisites
Electricity and Magnetism, Part 11 7 weeks 8-10 hours/week calculus, basic mechanics
Electricity and Magnetism, Part 2 7 weeks 8-10 hours/week Electricity and Magnetism, Part 1
Computation Structures 1: Digital Circuits2 10 weeks 6 hours/week electricity, magnetism
Computation Structures 2: Computer Architecture 10 weeks 6 hours/week Computation Structures 1
Computation Structures 3: Computer Organization 10 weeks 6 hours/week Computation Structures 2
ops-class.org - Hack the Kernel 15 weeks 6 hours/week algorithms

1 Note: These courses assume knowledge of basic physics; if you are struggling, you can find a physics MOOC or utilize the materials from Khan Academy: Khan Academy - Physics

2 Note: A shorter, less intense (but still very advanced) alternative to Computation Structures is here: Computer Architecture

Advanced theory

Topics covered: formal languages; Turing machines; computability; computational geometry theory; propositional logic; relational logic; Herbrand logic; concept lattices; game trees; and more.

Courses Duration Effort Prerequisites
Introduction to Logic 10 weeks 4-8 hours/week set theory
Automata Theory 8 weeks 10 hours/week discrete mathematics, logic, algorithms
Computational Geometry 16 weeks 8 hours/week algorithms, C++
Introduction to Formal Concept Analysis 6 weeks 4-6 hours/week logic, probability
Game Theory 8 weeks x hours/week mathematical thinking, probability, calculus

Advanced applications

These Coursera Specializations all end with a Capstone project. Depending on the course, you may be able to utilize the Capstone as your Final Project for this Computer Science curriculum. Note that doing a Specialization with the Capstone at the end always costs money. So if you don't wish to spend money or use the Capstone as your Final, it may be possible to take the courses in the Specialization for free by manually searching for them, but not all allow this.

Courses Duration Effort Prerequisites
Robotics (Specialization) 26 weeks 2-5 hours/week linear algebra, calculus, programming, probability
Data Mining (Specialization) 30 weeks 2-5 hours/week machine learning
Big Data (Specialization) 30 weeks 3-5 hours/week none
Internet of Things (Specialization) 30 weeks 1-5 hours/week strong programming
Cloud Computing (Specialization) 30 weeks 2-6 hours/week C++ programming
Full Stack Web Development (Specialization) 27 weeeks 2-6 hours/week programming, databases
Data Science (Specialization) 43 weeks 1-6 hours/week none

Final project

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.

After you've gotten through all of Core CS and the parts of Advanced CS relevant to you, you should think about a problem that you can solve using the knowledge you've acquired. Not only does real project work look great on a resume, the project will validate and consolidate your knowledge.

Another option is using the Capstone project from taking one of the Specializations in Advanced applications; whether or not this makes sense depends on the course, the project, and whether or not the course's Honor Code permits you to display your work publicly. In some cases, it may not be permitted; do not violate your course's Honor Code!

The final 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>

Cooperative work

You can create this project alone or with other students! We love cooperative work! Use our channels to communicate with other fellows to combine and create new projects!

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.

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 final project.

The important thing is to internalize the core concepts and to be able to use them with whatever tool (programming language) that you wish.

Pro CS

After completing the requirements of the curriculum above, you will have completed the equivalent of a full bachelor's degree in Computer Science, or quite close to one. 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. Many of these courses are graduate-level.

Choose one or more of the following specializations:

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

Where to go next?

  • Look for a job as a developer!
  • Check out the readings for classic books you can read that will sharpen your skills and expand your knowledge.
  • Join a local developer meetup (e.g. via Meetups.com).
  • Pay attention to emerging technologies in the world of software development, such as:
    • Elixir, a new functional programming language for the web based on the battle-tested BEAM VM!
    • Rust, a systems language which uses borrowing and lifetimes to achieve memory safety without a garbage collector!

keep learning

How to use this guide

Order of the classes

This guide was developed to be flexible. Ideally, Core CS 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. However, with very few exceptions, everything in Core CS should be completed before you begin Advanced CS. Pay attention to prerequisites.

Cost of the classes

No promises are made about the cost of any of the courses.

The web is utterly filled with free educational material if you are willing to spend the time looking for it; this curriculum has specifically been designed to prioritize quality over low cost. Nevertheless, the reality is that the professors who have made these courses and the platforms who host them are extraordinarily generous. The content of virtually every course on Coursera and edX is available at no charge, but if you want graded assignments and quizzes, you may have to pay, depending on the course; yet, these sums of money are nothing compared to the cost of attending their prestigious instutitions. Coursera is the platform upon which you are most likely to encounter paywalled features, but they offer financial aid to those eligible.

Some course materials are also available separate from these platforms, such as on YouTube. Below is a list of courses from the curriculum which have dedicated websites with freely available materials separate from the platforms:

Just remember that purchasing a course might save you some time and give you some extra motivation, but you cannot buy your way to success in this field. It's encouraged more as a way to thank the professor for their work. The most diligent students will be the most successful, regardless of how much or how little they spend.

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.

Content Policy

If you plan on showing off some of your coursework publicly, 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!

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.

Stay tuned

Watch this repository for futures improvements and general information.

Prerequisites

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!

Changelog

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