![Open Source Society University (OSSU)](http://i.imgur.com/h8xjrrj.png)
Path to a free self-taught education in Computer Science!
## Contents - [About](#about) - [Becoming an OSS student](#becoming-an-oss-student) - [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) - [Next Goals](#next-goals) - [References](#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) style 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](https://github.com/open-source-society/computer-science/issues/259) issue. > **"How can I do this?"** Comment in [this](https://github.com/open-source-society/computer-science/issues/259) 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?"** This is 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. You are free to bypass this if you're not that type. ## 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](http://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 - [Introduction to Computer Science](#introduction-to-computer-science) - [Math (Mathematical Thinking)](#math-mathematical-thinking) - [Program Design](#program-design) - [Math (Discrete Math)](#math-discrete-math) - [Algorithms](#algorithms) - [Programming Paradigms](#programming-paradigms) - [Software Testing](#software-testing) - [Math (Calculus)](#math-calculus) - [Software Architecture](#software-architecture) - [Theory](#theory) - [Software Engineering](#software-engineering) - [Math (Probability)](#math-probability) - [Computer Architecture](#computer-architecture) - [Operating Systems](#operating-systems) - [Computer Networks](#computer-networks) - [Databases](#databases) - [Cloud Computing](#cloud-computing) - [Math (Linear Algebra)](#math-linear-algebra) - [Cryptography](#cryptography) - [Security](#security) - [Compilers](#compilers) - [Parallel Computing](#parallel-computing) - [UX Design](#ux-design) - [Computer Graphics](#computer-graphics) - [Artificial Intelligence](#artificial-intelligence) - [Machine Learning](#machine-learning) - [Natural Language Processing](#natural-language-processing) - [Big Data](#big-data) - [Data Mining](#data-mining) - [Internet of Things](#internet-of-things) - [Specializations](#specializations) --- ### Introduction to Computer Science Courses | Duration | Effort :-- | :--: | :--: [Introduction to Computer Science and Programming Using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-5#!)| 9 weeks | 15 hours/week [From Nand to Tetris (Part 1) ](https://www.coursera.org/learn/build-a-computer) | 6 weeks | 5-10 hours/week ### Math (Mathematical Thinking) Courses | Duration | Effort :-- | :--: | :--: [Effective Thinking Through Mathematics](https://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01x) | 9 weeks | 5 hours/week ### Program Design Courses | Duration | Effort :-- | :--: | :--: [How to Code: Systematic Program Design - Part 1](https://www.edx.org/course/how-code-systematic-program-design-part-ubcx-spd1x)| 5 weeks | 8-12 hours/week [How to Code: Systematic Program Design - Part 2](https://www.edx.org/course/how-code-systematic-program-design-part-ubcx-spd2x)| 5 weeks | 8-12 hours/week [How to Code: Systematic Program Design - Part 3](https://www.edx.org/course/how-code-systematic-program-design-part-ubcx-spd3x)| 5 weeks | 8-12 hours/week ### Math (Discrete Math) Courses | Duration | Effort :-- | :--: | :--: [Mathematics for Computer Science](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/index.htm)| 12 weeks | 5 hours/week ### Algorithms Courses | Duration | Effort :-- | :--: | :--: [Algorithms, Part I](https://www.coursera.org/course/algs4partI)| 6 weeks | 6-12 hours/week [Algorithms, Part II](https://www.coursera.org/course/algs4partII)| 6 weeks | 6-12 hours/week ### Programming Paradigms Courses | Duration | Effort :-- | :--: | :--: [Functional Programming Principles in Scala](https://www.coursera.org/course/progfun)| 7 weeks | 5-7 hours/week [Object Oriented Programming in Java](https://www.coursera.org/learn/object-oriented-java) | 6 weeks | 4-6 hours/week ### Software Testing Courses | Duration | Effort :-- | :--: | :--: [Software Testing](https://www.udacity.com/course/software-testing--cs258)| 4 weeks | 6 hours/week [Software Debugging](https://www.udacity.com/course/software-debugging--cs259)| 8 weeks | 6 hours/week ### Math (Calculus) Courses | Duration | Effort :-- | :--: | :--: [Calculus One](https://www.coursera.org/learn/calculus1)| 16 weeks | 8-10 hours/week [Calculus Two: Sequences and Series](https://www.coursera.org/learn/advanced-calculus)| 7 weeks | 9-10 hours/week ### Software Architecture Courses | Duration | Effort :-- | :--: | :--: [Software Architecture & Design](https://www.udacity.com/course/software-architecture-design--ud821)| 8 weeks | 6 hours/week ### Theory Courses | Duration | Effort :-- | :--: | :--: [Automata](https://www.coursera.org/course/automata)| 6 weeks | 8-10 hours/week ### Software Engineering Courses | Duration | Effort :-- | :--: | :--: [Software Processes and Agile Practices](https://www.coursera.org/learn/software-processes-and-agile-practices)| 4 weeks | 6-8 hours/week ### Math (Probability) Courses | Duration | Effort :-- | :--: | :--: [Introduction to Probability - The Science of Uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-0)| 16 weeks | 12 hours/week ### Computer Architecture Courses | Duration | Effort :-- | :--: | :--: [Computer Architecture](https://www.coursera.org/course/comparch)| - | 5-8 hours/week ### Operating Systems Courses | Duration | Effort :-- | :--: | :--: [Operating Systems and System Programming](https://www.youtube.com/view_play_list?p=-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c)| 10 weeks | 2-3 hours/week ### Computer Networks Courses | Duration | Effort :-- | :--: | :--: [Computer Networks](https://www.coursera.org/course/comnetworks)| - | 4–12 hours/week ### Databases Courses | Duration | Effort :-- | :--: | :--: [Databases](https://lagunita.stanford.edu/courses/DB/2014/SelfPaced/about)| 12 weeks | 8-12 hours/week ### Cloud Computing Courses | Duration | Effort :-- | :--: | :--: [Introduction to Cloud Computing](https://www.edx.org/course/introduction-cloud-computing-ieeex-cloudintro-x-0)| 4 weeks | 1 hour/week ### Math (Linear Algebra) Courses | Duration | Effort :-- | :--: | :--: [Coding the Matrix: Linear Algebra through Computer Science Applications](https://www.coursera.org/course/matrix)| 10 weeks | 7-10 hours/week ### Cryptography Courses | Duration | Effort :-- | :--: | :--: [Cryptography I](https://www.coursera.org/course/crypto)| 6 weeks | 5-7 hours/week [Cryptography II](https://www.coursera.org/course/crypto2)| 6 weeks | 6-8 hours/week ### Security Courses | Duration | Effort :-- | :--: | :--: [Introduction to Cyber Security](https://www.futurelearn.com/courses/introduction-to-cyber-security) | 8 weeks | 3 hours/week ### Compilers Courses | Duration | Effort :-- | :--: | :--: [Compilers](https://www.coursera.org/course/compilers)| 9 weeks | 6-8 hours/week ### Parallel Computing Courses | Duration | Effort :-- | :--: | :--: [Heterogeneous Parallel Programming](https://www.coursera.org/course/hetero)| 11 weeks | 8-10 hours/week ### UX Design Courses | Duration | Effort :-- | :--: | :--: [UX Design for Mobile Developers](https://www.udacity.com/course/ux-design-for-mobile-developers--ud849)| 6 weeks | 6 hours/week ### Computer Graphics Courses | Duration | Effort :-- | :--: | :--: [Computer Graphics](https://www.edx.org/course/computer-graphics-uc-san-diegox-cse167x)| 6 weeks | 12 hours/week ### Artificial Intelligence Courses | Duration | Effort :-- | :--: | :--: [Artificial Intelligence](https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1x#!)| 12 weeks | 15 hours/week ### Machine Learning Courses | Duration | Effort :-- | :--: | :--: [Machine Learning](https://www.coursera.org/learn/machine-learning)| 11 weeks | 4-6 hours/week ### Natural Language Processing Courses | Duration | Effort :-- | :--: | :--: [Natural Language Processing](https://www.coursera.org/course/nlangp)| 10 weeks | 8-10 hours/week ### Big Data Courses | Duration | Effort :-- | :--: | :--: [Introduction to Big Data](https://www.coursera.org/learn/intro-to-big-data)| 3 weeks | 5-6 hours/week ### Data Mining Courses | Duration | Effort :-- | :--: | :--: [Pattern Discovery in Data Mining](https://www.coursera.org/course/patterndiscovery) | 4 weeks | 4-6 hours/week ### Internet of Things Courses | Duration | Effort :-- | :--: | :--: [The Internet of Things](https://www.futurelearn.com/courses/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. 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) ![keep learning](http://i.imgur.com/REQK0VU.jpg) ## 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 to Computer Science](#introduction-to-computer-science) 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](http://jamesclear.com/goals-systems). ### 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 world 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](https://github.com/open-source-society/help/blob/master/PROJECTS.md) file. Submit your project's information in that file after you conclude it. **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 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](#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**: `2.0.0` 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 **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](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! =)** ## 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! [![Join the chat at https://gitter.im/open-source-society/computer-science](https://badges.gitter.im/Join%20Chat.svg)](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**. ## Next Goals - [Add our University page at Linkedin](https://help.linkedin.com/app/answers/detail/a_id/40128/~/adding-a-new-university-page), so in that way we will be able to add **OSS University** in our Linkedin profile. ## 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/) - [Future Learn](https://www.futurelearn.com/) - [Stanford University](https://lagunita.stanford.edu/) - [MIT Open Courseware](http://ocw.mit.edu/courses/#electrical-engineering-and-computer-science) - [Obtaining a Thorough CS Background Online](http://spin.atomicobject.com/2015/05/15/obtaining-thorough-cs-background-online/)