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315 lines
12 KiB
Markdown
315 lines
12 KiB
Markdown
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![open source society university](http://i.imgur.com/h8xjrrj.png)
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:mortar_board: **Path to a free self-taught graduation in Computer Science!**
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## Contents
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- [About](#about)
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- [Becoming an OSS student](#becoming-an-oss-student)
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- [Topics](#topics)
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- [How to use this guide](#how-to-use-this-guide)
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- [Prerequisite](#prerequisite)
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- [How to collaborate](#how-to-collaborate)
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- [Community](#community)
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- [Next Goals](#next-goals)
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- [References](#references)
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## About
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This is a **solid path** for you that want to graduate in a Computer Science course in your own time, **for free**, with courses from the **best universities** of the World.
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Here we will <strike>try to</strike> choose a maximum of **3** courses for each category. Futurely, more categories and/or courses can be added to this list or in a more advanced list.
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Initially, we will also give preference for MOOC (Massive Open Online Course) type of courses because those courses were created with our style of learning in mind.
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## Becoming an OSS student
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Your registration for this graduation course will be effectuated after you create your profile in our [students](/students) folder.
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> **"How can I do this?"**
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Just fork this repository and create a markdown file named with your **GitHub username**. It’s that simple.
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Use the model below to create your own file:
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```
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# Student Profile
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- **Name**: YOUR NAME
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- **GitHub**: [@your_username]()
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- **Twitter**: [@your_username]()
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- **Linkedin**: [link]()
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- **Website**: [yourblog.com]()
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# Completed Courses
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**Name of the Section**
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Course|Files
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Course Name| [link]()
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```
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**ps**: In the *Completed Courses* section, you should link your repository that contain the files that you created in the respective course.
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> **"Why should I do this?"**
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Making a [public commitment](http://renewablewealth.com/articles/the-power-of-a-public-commitment/), we have much more chances to **succeed** in our graduation, know better our fellows and share the things that we have done.
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For those reasons we are using that strategy.
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---
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## Topics
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- [Introduction](#introduction)
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- [Program Design](#program-design)
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- [Programming Paradigms](#programming-paradigms)
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- [Software Testing](#software-testing)
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- [Math](#math)
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- [Algorithms](#algorithms)
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- [Software Architecture](#software-architecture)
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- [Software Engineering](#software-engineering)
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- [Operating Systems](#operating-systems)
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- [Computer Networks](#computer-networks)
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- [Databases](#databases)
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- [Cloud Computing](#cloud-computing)
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- [Cryptography](#cryptography)
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- [Compilers](#compilers)
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- [UX Design](#ux-design)
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- [Artificial Intelligence](#artificial-intelligence)
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- [Machine Learning](#machine-learning)
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- [Natural Language Processing](#natural-language-processing)
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- [Big Data](#big-data)
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- [Data Mining](#data-mining)
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---
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### Introduction
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Course|Duration
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[Introduction to Computer Science](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#!)| 9 ~ 15 weeks
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[Introduction to Computer Science and Programming Using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-5#!)| 9 weeks
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[Introduction to Computational Thinking and Data Science](https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-2#!)| 10 weeks
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### Program Design
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Course|Duration
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[Systematic Program Design- Part 1: The Core Method](https://www.edx.org/course/systematic-program-design-part-1-core-ubcx-spd1x-0)| 5 weeks
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[Systematic Program Design- Part 2: Arbitrary Sized Data](https://www.edx.org/course/systematic-program-design-part-2-ubcx-spd2x)| 5 weeks
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[Systematic Program Design- Part 3: Abstraction, Search and Graphs](https://www.edx.org/course/systematic-program-design-part-3-ubcx-spd3x)| 5 weeks
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### Programming Paradigms
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Course|Duration
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[Introduction to Functional Programming](https://www.edx.org/course/introduction-functional-programming-delftx-fp101x-0#ct-read-review-widget)| 7 weeks
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[Principles of Reactive Programming](https://www.coursera.org/course/reactive)| 7 weeks
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[Programming Languages](https://www.coursera.org/course/proglang)| 8-16 hours/week
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[Functional Programming Principles in Scala](https://www.coursera.org/course/progfun)| 7 weeks
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### Software Testing
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Course|Duration
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[Software Testing](https://www.udacity.com/course/software-testing--cs258)| 4 weeks
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[Software Debugging](https://www.udacity.com/course/software-debugging--cs259)| 8 weeks
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### Math
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Course|Duration
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[Effective Thinking Through Mathematics](https://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01x)| 9 weeks
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[Applications of Linear Algebra Part 1](https://www.edx.org/course/applications-linear-algebra-part-1-davidsonx-d003x-1#ct-read-review-widget)| 5 weeks
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[Applications of Linear Algebra Part 2](https://www.edx.org/course/applications-linear-algebra-part-2-davidsonx-d003x-2)| 4 weeks
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[Linear and Discrete Optimization](https://www.coursera.org/course/linearopt)| 3-6 hours/week
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[Probabilistic Graphical Models](https://www.coursera.org/course/pgm)| 11 weeks
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[Game Theory](https://www.coursera.org/course/gametheory)| 9 weeks
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### Algorithms
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Course|Duration
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[Algorithms, Part I](https://www.coursera.org/course/algs4partI)| 6 weeks
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[Algorithms, Part II](https://www.coursera.org/course/algs4partII)| 6 weeks
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[Analysis of Algorithms](https://www.coursera.org/course/aofa)| 6 weeks
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### Software Architecture
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Course|Duration
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[Web Application Architectures](https://www.coursera.org/course/webapplications)| 6-9 hours/week
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[Software Architecture & Design](https://www.udacity.com/course/software-architecture-design--ud821)| -
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[Microservice Architectures TODO]()| -
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### Software Engineering
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Course|Duration
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[Engineering Software as a Service (SaaS), Part 1](https://www.edx.org/course/engineering-software-service-saas-part-1-uc-berkeleyx-cs169-1x)| 9 weeks
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[Engineering Software as a Service (Saas), Part 2](https://www.edx.org/course/engineering-software-service-saas-part-2-uc-berkeleyx-cs169-2x)| 8 weeks
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[Software Product Management Specialization](https://www.coursera.org/specializations/product-management)| -
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### Operating Systems
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Course|Duration
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[Operating System Engineering](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-828-operating-system-engineering-fall-2012/)| -
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[Operating Systems and System Programming](https://www.youtube.com/watch?v=XgQo4JkN4Bw&list=PL3289DD0D0F0CD4A3)| -
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### Computer Networks
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Course|Duration
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[Computer Networks](https://www.coursera.org/course/comnetworks)| 4–12 hours/week
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[Software Defined Networking](https://www.coursera.org/course/sdn1)| 7-10 hours/week
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### Databases
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Course|Duration
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[Introduction to Databases](https://www.coursera.org/course/db)| -
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[Database Design](https://www.udemy.com/database-design/#reviews)| 9 hours
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[Database Management Essentials](https://www.coursera.org/learn/database-management)| weeks
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### Cloud Computing
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Course|Duration
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[Introduction to Cloud Computing](https://www.edx.org/course/introduction-cloud-computing-ieeex-cloudintro-x-0)| 4 weeks
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[Cloud Computing Specialization](https://www.coursera.org/specializations/cloudcomputing)| -
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### Cryptography
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Course|Duration
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[Cryptography I](https://www.coursera.org/course/crypto)| 6 weeks
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[Cryptography II](https://www.coursera.org/course/crypto2)| 6 weeks
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[Applied Cryptography](https://www.udacity.com/course/applied-cryptography--cs387)| 8 weeks
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### Compilers
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Course|Duration
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[Compilers](https://www.coursera.org/course/compilers)| 11 weeks
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### UX Design
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Course|Duration
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[Interaction Design Specialization](https://www.coursera.org/specializations/interaction-design)| -
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[UX Design for Mobile Developers](https://www.udacity.com/course/ux-design-for-mobile-developers--ud849)| 6 weeks
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### Artificial Intelligence
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Course|Duration
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[Artificial Intelligence](https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1x#!)| 12 weeks
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### Machine Learning
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Course|Duration
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[Practical Machine Learning](https://www.coursera.org/course/predmachlearn)| 4 weeks
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[Machine Learning](https://www.coursera.org/learn/machine-learning)| 11 weeks
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[Neural Networks for Machine Learning](https://www.coursera.org/course/neuralnets)| 8 weeks
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### Natural Language Processing
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Course|Duration
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[Natural Language Processing](https://www.coursera.org/course/nlangp)| 10 weeks
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[Natural Language Processing](https://www.coursera.org/course/nlp)| 10 weeks
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### Big Data
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Course|Duration
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[Big Data Specialization](https://www.coursera.org/specializations/big-data)| -
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### Data Mining
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Course|Duration
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[Data Mining specialization](https://www.coursera.org/specializations/datamining)| -
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## How to use this guide
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### Order of the classes
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This guide was developed to be consumed in a linear approach. What this means? That you should do one course at a time.
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The courses already **are** in the order that you should consume them. Just start in the **Introduction** section and after finishing the first course, start the next one.
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**If the course isn't open, do it anyway with the resources from the previous class.**
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### Should I take all courses?
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**Yes**! The intention is to conclude **all** the courses listed here!
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### Duration of the project
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Maybe to finish all the classes we will spend **more time** than with a regular CS course, but I can **guarantee** to you that your **reward** will be proportional to **your motivation/dedication**!
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### How can I track my progress?
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You should create a repository on GitHub to put all files that you created for each course.
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You can create one repository for each course, or just one repository that will contain all files for all courses. The first option is our preferred approach.
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### Cooperative work
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**We love cooperative work**! But is quite difficult manage a large base of students with specific projects. Use our channels to communicate with other fellows and to combine and create new projects.
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### Which programming languages should I use?
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My friend here is the awesome part of the liberty! You can use **any** language that you want to complete the courses.
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The **important** thing for each course is to **internalize** the **core concepts** and be able to use them with whatever tool (programming language) that you touch.
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### Stay tuned
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[Watch](https://help.github.com/articles/watching-repositories/) this repository for futures improvements and general information.
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## Prerequisite
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The **only thing** that you need to know is how to use **Git** and **GitHub**. Here are some resources to learn about them:
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- [Try Git](https://try.github.io/levels/1/challenges/1)
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- [GitHub Training & Guides](https://www.youtube.com/playlist?list=PLg7s6cbtAD15G8lNyoaYDuKZSKyJrgwB-)
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- [GitHub Hello World](https://guides.github.com/activities/hello-world/)
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- [Git Immersion](http://gitimmersion.com/index.html)
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- [How to Use Git and GitHub](https://www.udacity.com/course/how-to-use-git-and-github--ud775)
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**ps**: You don't need to do all that courses. Just pick one of them, learn the minimal because the other things you will learn on the go!
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## How to collaborate
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You can [open an issue](https://help.github.com/articles/creating-an-issue/) and give your suggestion to how we could improve this guide, or what we can do to improve the learning experience.
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You can also fork this project and fix any mistakes that you have found.
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Let's do it together! =)
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## Community
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Join us in our [group](https://groups.google.com/forum/#!forum/open-source-society-university)!
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You can also interact through [GitHub issues](https://github.com/open-source-society/computer-science-and-engineering/issues).
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> **ps**: A forum is an ideal way to interact with other students because in that way we do not lose important discussions, as occur usually in communication via chat apps.
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## Next Goals
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- [Adding 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.
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## References
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- [Google - Guide for Technical Development](https://www.google.com/about/careers/students/guide-to-technical-development.html)
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- [Coursera](https://www.coursera.org/)
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- [edX](https://www.edx.org)
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- [MIT Open Courseware](http://ocw.mit.edu/courses/#electrical-engineering-and-computer-science)
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