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</a>
</p>
## Contents
# Contents
- [About](#about)
- [Motivation & Preparation](#motivation--preparation)
@ -25,13 +25,13 @@
- [Team](#team)
- [References](#references)
## About
# 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
# Motivation & Preparation
Here are two interesting links that can make **all** the difference in your journey.
@ -45,253 +45,105 @@ The second link is a MOOC that will teach you learning techniques used by expert
**Are you ready to get started?**
## Curriculum
# Curriculum
- [Introduction to Computer Science](#introduction-to-computer-science)
- [Math (Mathematical Thinking)](#math-mathematical-thinking)
- [Program Design](#program-design)
- [Math (Calculus & Discrete Math)](#math-calculus-and-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)
- [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)
---
### Introduction to Computer Science
## Core CS
### Core programming
Courses | Duration | Effort
:-- | :--: | :--:
[Introduction to Computer Science - CS50](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#!)| 12 weeks | 10-20 hours/week
[How to Code: Systematic Program Design (XSeries)](https://www.edx.org/xseries/how-code-systematic-program-design) | 15 weeks | 5 hours/week
[Object Oriented Programming in Java](https://www.coursera.org/learn/object-oriented-java) | 6 weeks | 4-6 hours/week
[Programming Languages, Part A](https://www.coursera.org/learn/programming-languages) | 4 weeks | 8-16 hours/week
[Programming Languages, Part B](https://www.coursera.org/learn/programming-languages-part-b) | 3 weeks | 8-16 hours/week
[Programming Languages, Part C](https://www.coursera.org/learn/programming-languages-part-c) | 3 weeks | 8-16 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) | 4 weeks | 2-5 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 (Calculus and Discrete Math)
### Core math
Courses | Duration | Effort
:-- | :--: | :--:
[Calculus One](https://www.coursera.org/learn/calculus1)| 16 weeks | 8-10 hours/week
[Mathematics for Computer Science](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-spring-2015/index.htm)| 12 weeks | 5 hours/week
### Algorithms
[Calculus Two: Sequences and Series](https://www.coursera.org/learn/advanced-calculus)| 7 weeks | 9-10 hours/week
[Introduction to Probability - The Science of Uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2) | 18 weeks | 12 hours/week
[Discrete Mathematics](https://www.coursera.org/learn/discrete-mathematics) | 11 weeks | 3-5 hours/week
[Linear Algebra - Foundations to Frontiers](https://www.edx.org/course/linear-algebra-foundations-frontiers-utaustinx-ut-5-04x#!)| 15 weeks | 8 hours/week
### Core systems
Courses | Duration | Effort
:-- | :--: | :--:
[Algorithms, Part I](https://www.coursera.org/learn/algorithms-part1)| 6 weeks | 6-12 hours/week
[Algorithms, Part II](https://www.coursera.org/learn/algorithms-part2)| 6 weeks | 6-12 hours/week
### Programming Paradigms
[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
[Build a Modern Computer from First Principles: Nand to Tetris Part II ](https://www.coursera.org/learn/nand2tetris2) | 6 weeks | 12-18 hours/week
[Databases](https://lagunita.stanford.edu/courses/DB/2014/SelfPaced/about)| 12 weeks | 8-12 hours/week
[Introduction to Computer Networking](https://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about)| - | 4–12 hours/week
### Core theory
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
[Divide and Conquer, Sorting and Searching, and Randomized Algorithms](https://www.coursera.org/learn/algorithms-divide-conquer) | 4 weeks | 4-8 hours/week
[Graph Search, Shortest Paths, and Data Structures](https://www.coursera.org/learn/algorithms-graphs-data-structures) | 4 weeks | 4-8 hours/week
[Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming](https://www.coursera.org/learn/algorithms-greedy) | 4 weeks | 4-8 hours/week
[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
[Automata Theory](https://lagunita.stanford.edu/courses/course-v1:ComputerScience+Automata+Fall2016/about) | 8 weeks | 10 hours/week
### Software Testing
### Core applications
Courses | Duration | Effort
:-- | :--: | :--:
[Machine Learning](https://www.coursera.org/learn/machine-learning)| 11 weeks | 4-6 hours/week
[Computer Graphics](https://www.edx.org/course/computer-graphics-uc-san-diegox-cse167x)| 6 weeks | 12 hours/week
[Cryptography I](https://www.coursera.org/course/crypto)| 6 weeks | 5-7 hours/week
### Advanced programming
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 Two: Sequences and Series](https://www.coursera.org/learn/advanced-calculus)| 7 weeks | 9-10 hours/week
### Software Architecture
Courses | Duration | Effort
:-- | :--: | :--:
[Introduction to Parallel Programming](https://www.udacity.com/course/intro-to-parallel-programming--cs344) | 12 weeks | -
[Software Architecture & Design](https://www.udacity.com/course/software-architecture-design--ud821)| 8 weeks | 6 hours/week
### Theory
## Electives
Courses | Duration | Effort
:-- | :--: | :--:
[Intro to Theoretical Computer Science](https://www.udacity.com/course/intro-to-theoretical-computer-science--cs313)| 9 weeks | 6 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://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about)| - | 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
:-- | :--: | :--:
[Linear Algebra - Foundations to Frontiers](https://www.edx.org/course/linear-algebra-foundations-frontiers-utaustinx-ut-5-04x#!)| 15 weeks | 8 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://lagunita.stanford.edu/courses/Engineering/Compilers/Fall2014/about)| 9 weeks | 6-8 hours/week
### Parallel Computing
Courses | Duration | Effort
:-- | :--: | :--:
[Parallel Computer Architecture and Programming](http://15418.courses.cs.cmu.edu/spring2016/home)| 20 weeks | -
### 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
:-- | :--: | :--:
[Introduction to Natural Language Processing](https://www.coursera.org/learn/natural-language-processing)| 12 weeks | -
### Big Data
Courses | Duration | Effort
:-- | :--: | :--:
[Introduction to Big Data](https://www.coursera.org/learn/big-data-introduction)| 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
## 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)
### 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
# How to use this guide
### Order of the classes
## 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.
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.
The courses are **already** in the order 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.
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.
**OBS:** If the course is not open, do it with the archived resources or wait until next class is open.
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
## 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/).
@ -309,19 +161,23 @@ We also have **labels** to help you have more control through the process. The m
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?
## Should I take all courses?
**Yes!** The intention is to conclude **all** the courses listed here!
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.
### Duration of the project
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.
It may take longer to complete all courses compared to a regular CS graduation, but I can **guarantee** you that your **reward** will be proportional to your extra **effort**!
## 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
## Project Based
Here in **OSS University**, you do **not** need to take exams, because we are focused on **real projects**!
@ -340,7 +196,7 @@ Put the OSSU-CS badge in the README of your repository! [![Open Source Society U
**You can create this project alone or with other students!**
#### Project Suggestions
### 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.
@ -349,7 +205,7 @@ Put the OSSU-CS badge in the README of your repository! [![Open Source Society U
And you should also...
### Be creative!
## Be creative!
This is a **crucial** part of your journey through all those courses.
@ -362,27 +218,27 @@ 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
## 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?
## 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.
My friend, here is the best part of liberty! You can use **any** language that you want to complete the
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
## 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
## Stay tuned
[Watch](https://help.github.com/articles/watching-repositories/) this repository for futures improvements and general information.
## Prerequisite
# Prerequisite
The **only things** that you need to know are how to use **Git** and **GitHub**. Here are some resources to learn about them:
@ -395,7 +251,7 @@ The **only things** that you need to know are how to use **Git** and **GitHub**.
- [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
# Change Log
**Curriculum Version**: `6.0`
@ -407,7 +263,7 @@ Our students can **trust** in this curriculum because it has been **carefully pl
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/Developer.
## How to collaborate
# 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.
@ -419,7 +275,7 @@ The **extras** section is a place where all of us will be able to submit interes
**Let's do it together! :smile:**
## Community
# Community
Subscribe to [/r/opensourcesociety](https://www.reddit.com/r/opensourcesociety/)!
@ -433,13 +289,13 @@ Add **Open Source Society University** to your [Facebook](https://www.facebook.c
> **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
# 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
# References
- [Google - Guide for Technical Development](https://www.google.com/about/careers/students/guide-to-technical-development.html)
- [Coursera](https://www.coursera.org/)