Open Source Society University
Path to a self-taught education in Computer Science!
# Contents
- [About](#about)
- [Motivation & Preparation](#motivation--preparation)
- [Curriculum](#curriculum)
- [How to use this guide](#how-to-use-this-guide)
- [Prerequisite](#prerequisite)
- [How to collaborate](#how-to-collaborate)
- [Community](#community)
- [Team](#team)
- [References](#references)
# 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**.
- [MIT Challenge](https://www.scotthyoung.com/blog/myprojects/mit-challenge-2/)
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.
- [Learning How to Learn](https://www.coursera.org/learn/learning-how-to-learn)
**Are you ready to get started?**
# Curriculum
- [Core CS](#core-cs)
- [Core programming](#core-programming)
- [Core math](#core-math)
- [Core systems](#core-systems)
- [Core theory](#core-theory)
- [Core applications](#core-applications)
- [Advanced programming](#advanced-programming)
- [Electives](#electives)
- [Specializations](#specializations)
---
## Core CS
### Core programming
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Introduction to Computer Science - CS50](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#!)| 12 weeks | 10-20 hours/week | none
[How to Code: Systematic Program Design (XSeries)](https://www.edx.org/xseries/how-code-systematic-program-design) | 15 weeks | 5 hours/week | none
[Object Oriented Programming in Java](https://www.coursera.org/learn/object-oriented-java) | 6 weeks | 4-6 hours/week | some programming
[Programming Languages, Part A](https://www.coursera.org/learn/programming-languages) | 4 weeks | 8-16 hours/week | recommended: Java, C
[Programming Languages, Part B](https://www.coursera.org/learn/programming-languages-part-b) | 3 weeks | 8-16 hours/week | Programming Languages, Part A
[Programming Languages, Part C](https://www.coursera.org/learn/programming-languages-part-c) | 3 weeks | 8-16 hours/week | Programming Languages, Part B
### Core math
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Introduction to Mathematical Thinking](https://www.coursera.org/learn/mathematical-thinking) | 10 weeks | 10 hours/week | high school math
[Calculus One](https://www.coursera.org/learn/calculus1)| 16 weeks | 8-10 hours/week | pre-calculus
[Calculus Two: Sequences and Series](https://www.coursera.org/learn/advanced-calculus)| 7 weeks | 9-10 hours/week | Calculus One
[Introduction to Probability - The Science of Uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2) | 18 weeks | 12 hours/week | calculus
[Discrete Mathematics](https://www.coursera.org/learn/discrete-mathematics) | 11 weeks | 3-5 hours/week | high school math
[Linear Algebra - Foundations to Frontiers](https://www.edx.org/course/linear-algebra-foundations-frontiers-utaustinx-ut-5-04x#!)| 15 weeks | 8 hours/week | high school math
### Core systems
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Build a Modern Computer from First Principles: From Nand to Tetris](https://www.coursera.org/learn/build-a-computer) | 6 weeks | 7-13 hours/week | none
[Build a Modern Computer from First Principles: Nand to Tetris Part II ](https://www.coursera.org/learn/nand2tetris2) | 6 weeks | 12-18 hours/week | Part I
[Databases](https://lagunita.stanford.edu/courses/DB/2014/SelfPaced/about)| 12 weeks | 8-12 hours/week | some programming, basic CS
[Introduction to Computer Networking](https://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about)| - | 4–12 hours/week | probability, basic CS
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](https://smile.amazon.com/Computer-Organization-Design-Fifth-Architecture/dp/0124077269).
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](http://pages.cs.wisc.edu/~remzi/OSTEP/).
### Core theory
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Divide and Conquer, Sorting and Searching, and Randomized Algorithms](https://www.coursera.org/learn/algorithms-divide-conquer) | 4 weeks | 4-8 hours/week | one programming language; proofs; probability
[Graph Search, Shortest Paths, and Data Structures](https://www.coursera.org/learn/algorithms-graphs-data-structures) | 4 weeks | 4-8 hours/week | previous algorithms course
[Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming](https://www.coursera.org/learn/algorithms-greedy) | 4 weeks | 4-8 hours/week | previous algorithms course
[Shortest Paths Revisited, NP-Complete Problems and What To Do About Them](https://www.coursera.org/learn/algorithms-npcomplete) | 4 weeks | 4-8 hours/week | previous algorithms course
[Automata Theory](https://lagunita.stanford.edu/courses/course-v1:ComputerScience+Automata+Fall2016/about) | 8 weeks | 10 hours/week | discrete mathematics
### Core applications
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Machine Learning](https://www.coursera.org/learn/machine-learning)| 11 weeks | 4-6 hours/week | linear algebra
[Computer Graphics](https://www.edx.org/course/computer-graphics-uc-san-diegox-cse167x)| 6 weeks | 12 hours/week | C++ or Java, linear algebra
[Cryptography I](https://www.coursera.org/course/crypto)| 6 weeks | 5-7 hours/week | linear algebra; probability
### Advanced programming
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Software Testing](https://www.udacity.com/course/software-testing--cs258)| 4 weeks | 6 hours/week | some programming
[Software Debugging](https://www.udacity.com/course/software-debugging--cs259)| 8 weeks | 6 hours/week | Python, object-oriented programming
[Introduction to Parallel Programming](https://www.udacity.com/course/intro-to-parallel-programming--cs344) | 12 weeks | - | C, algorithms
[Software Architecture & Design](https://www.udacity.com/course/software-architecture-design--ud821)| 8 weeks | 6 hours/week | Java programming
## Electives
Courses | Duration | Effort | Prerequisites
:-- | :--: | :--: | :--:
[Cryptography II](https://www.coursera.org/course/crypto2)| 6 weeks | 6-8 hours/week | Cryptography I
[Compilers](https://lagunita.stanford.edu/courses/Engineering/Compilers/Fall2014/about)| 9 weeks | 6-8 hours/week | none
[Introduction to Natural Language Processing](https://www.coursera.org/learn/natural-language-processing)| 12 weeks | - | Python programming
## 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](https://www.edx.org/xseries)
### Coursera: [Specializations](https://www.coursera.org/specializations)
### Udacity: [Nanodegree](https://www.udacity.com/nanodegree)
### FutureLearn: [Collections](https://www.futurelearn.com/courses/collections)
# 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, and 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](https://trello.com/).
1. Copy [this](https://trello.com/b/9DPXYv5f) board to your personal account. See how to copy a board [here](http://blog.trello.com/you-can-copy-boards-now-finally/).
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](http://jamesclear.com/goals-systems).
## 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 are purely theoretical (e.g. calculus). 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](PROJECTS.md) file. **Submit your project's information in that file after you conclude it**.
Put the OSSU-CS badge in the README of your repository! [](https://github.com/open-source-society/computer-science)
- Markdown: `[](https://github.com/open-source-society/computer-science)`
- HTML: ``
**You can create this project alone or with other students!**
### Project Suggestions
- [Projects](https://github.com/karan/Projects): A list of practical projects that anyone can solve in any programming language.
- [app-specs](https://github.com/ericdouglas/app-specs): A curated list of applications specifications and implementations to practice new technologies, improve your portfolio and sharpen your skills.
- [FreeCodeCamp](http://www.freecodecamp.com/): Course that teaches you fullstack JavaScript development through a bunch of projects.
- [JavaScript Projects](https://github.com/javascript-society/javascript-projects): List of projects related with the [JavaScript Path](https://github.com/javascript-society/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](#community) 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](#be-creative) in order to show your progress! :smile:
## Stay tuned
[Watch](https://help.github.com/articles/watching-repositories/) 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](https://try.github.io/levels/1/challenges/1)
- [Git - the simple guide](http://rogerdudler.github.io/git-guide/)
- [GitHub Training & Guides](https://www.youtube.com/playlist?list=PLg7s6cbtAD15G8lNyoaYDuKZSKyJrgwB-)
- [GitHub Hello World](https://guides.github.com/activities/hello-world/)
- [Git Immersion](http://gitimmersion.com/index.html)
- [How to Use Git and GitHub](https://www.udacity.com/course/how-to-use-git-and-github--ud775)
# Change Log
**Curriculum Version**: `6.0`
To show respect to all of our students, we will keep a [CHANGELOG](CHANGELOG.md) 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](https://help.github.com/articles/creating-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](https://help.github.com/articles/fork-a-repo/) and send a [pull request](https://help.github.com/articles/using-pull-requests/) 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](https://github.com/open-source-society/computer-science/tree/master/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](https://www.reddit.com/r/opensourcesociety/)!
Join us in our [group](https://groups.google.com/forum/#!forum/open-source-society-university)!
You can also interact through [GitHub issues](https://github.com/open-source-society/computer-science/issues).
We also have a chat room! [](https://gitter.im/open-source-society/computer-science?utm_campaign=pr-badge&utm_content=badge&utm_medium=badge&utm_source=badge)
Add **Open Source Society University** to your [Facebook](https://www.facebook.com/ossuniversity) 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](https://github.com/ericdouglas)
* **Curriculum Maintainer**: [Eric Douglas](https://github.com/ericdouglas)
* **Contributors**: [contributors](https://github.com/open-source-society/computer-science/graphs/contributors)
# References
- [Google - Guide for Technical Development](https://www.google.com/about/careers/students/guide-to-technical-development.html)
- [Coursera](https://www.coursera.org/)
- [edX](https://www.edx.org)
- [Udacity](https://www.udacity.com/)
- [Stanford University](https://lagunita.stanford.edu/)
- [MIT Open Courseware](http://ocw.mit.edu/courses/#electrical-engineering-and-computer-science)
- [A DIY Computer Science Education](https://bradfieldcs.com/diy/)
- [Obtaining a Thorough CS Background Online](http://spin.atomicobject.com/2015/05/15/obtaining-thorough-cs-background-online/)