🎓 Path to a self-taught graduation in Computer Science!

Contents

• About
• Becoming an OSS student
• Topics
• Next Goals
• References

About

This is a solid path for you that want to graduate in a Computer Science course in your own time, for free, studying by courses from the best universities of the World.

Here we will try to 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.

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.

Becoming an OSS student

Your registration for this graduation course will be effectuated after you create your profile in our students folder.

"How can I do it?"

Just fork this repository and create a markdown file named with your GitHub username. It’s that simple.

Use the model below to create your own file:

# Student Profile

**Name**: YOUR NAME
**GitHub**: [@your_username]()
**Twitter**: [@your_username]()
**Linkedin**: [link]()

# Completed courses

**Name of the section**

Course||Files
:--|:--:
Course name| [link]()

---

Topics

• Introduction

• Program Design

• Programming Paradigms

• Software Testing

• Math

• Algorithms

• Software Architecture

• Software Engineering

• Operating Systems

• Networks

• Databases

• Cloud Computing

• Cryptography

• Compilers

• UX Design

• Artificial Intelligence

• Machine Learning

• Natural Language Processing

• Internet of Things

• Graphs

• Data Mining

• Programming Languages

---

Introduction

Course	Duration	Files	Status
Introduction to Computer Science	9 ~ 15 weeks	⎙	-
Introduction to Computer Science and Programming Using Python	9 weeks	⎙	-
Introduction to Computational Thinking and Data Science	10 weeks	⎙	-

Program Design

Course	Duration	Files	Status
Systematic Program Design- Part 1: The Core Method	5 weeks	⎙	-
Systematic Program Design- Part 2: Arbitrary Sized Data	5 weeks	⎙	-
Systematic Program Design- Part 3: Abstraction, Search and Graphs	5 weeks	⎙	-

Programming Paradigms

Course	Duration	Files	Status
Introduction to Functional Programming	7 weeks	⎙	-
Principles of Reactive Programming	7 weeks	⎙	-
Programming Languages	8-16 hours/week	⎙	-
Functional Programming Principles in Scala	7 weeks	⎙	-

Software Testing

Course	Duration	Files	Status
Software Testing	4 weeks	⎙	-
Software Debugging	8 weeks	⎙	-

Math

Course	Duration	Files	Status
Effective Thinking Through Mathematics	9 weeks	⎙	-
Applications of Linear Algebra Part 1	5 weeks	⎙	-
Applications of Linear Algebra Part 2	4 weeks	⎙	-
Linear and Discrete Optimization	3-6 hours/week	⎙	-
Probabilistic Graphical Models	11 weeks	⎙	-
Game Theory	9 weeks	⎙	-

Algorithms

Course	Duration	Files	Status
Algorithms, Part I	6 weeks	⎙	-
Algorithms, Part II	6 weeks	⎙	-
Analysis of Algorithms	6 weeks	⎙	-

Software Architecture

Course	Duration	Files	Status
Web Application Architectures	6-9 hours/week	⎙	-
Microservice Architectures TODO	-	⎙	-

Software Engineering

Course	Duration	Files	Status
Engineering Software as a Service (SaaS), Part 1	9 weeks	⎙	-
Engineering Software as a Service (Saas), Part 2	8 weeks	⎙	-
Software Product Management Specialization	-	⎙	-

Operating Systems

Course	Duration	Files	Status
Operating System Engineering	-	⎙	-
Operating Systems and System Programming	-	⎙	-

Networks

Course	Duration	Files	Status
Computer Networks	4–12 hours/week	⎙	-
Software Defined Networking	7-10 hours/week	⎙	-

Databases

Course	Duration	Files	Status
Introduction to Databases	-	⎙	-
Database Design	9 hours	⎙	-
Database Management Essentials	weeks	⎙	-

Cloud Computing

Course	Duration	Files	Status
Introduction to Cloud Computing	4 weeks	⎙	-
Cloud Computing Specialization	-	⎙	-

Cryptography

Course	Duration	Files	Status
	weeks	⎙	-
	weeks	⎙	-
	weeks	⎙	-

1. Cryptography I - ⎙
2. Applied Cryptography - ⎙

Compilers

1. Compilers - ⎙

Artificial Intelligence

1. Artificial Intelligence - ⎙

Machine Learning

1. Practical Machine Learning - ⎙
2. Machine Learning - ⎙
3. Neural Networks for Machine Learning - ⎙

Natural Language Processing

1. Natural Language Processing - ⎙
2. Natural Language Processing - ⎙

Internet of Things

Graphs

Data Mining

1. Data Mining - ⎙

Parallel Programming

1. Parallel Computing - ⎙
2. Heterogeneous Parallel Programming - ⎙

Programming Languages

1. Practical Programming in C - ⎙
2. Introduction to C Memory Management and C++ Object-Oriented Programming - ⎙
3. Effective Programming in C and C++ - ⎙

Others

1. Introduction to Functional Programming
2. Engineering Software as a Service
3. Engineering Software as a Service, Part 2
4. Automata, Computability, and Complexity - ⎙
5. Computational Biology: Genomes, Networks, Evolution - ⎙
6. Creating Video Games - ⎙
7. Computer Graphics - ⎙
8. User Interface Design and Implementation - ⎙
9. Making Sense of Data - ⎙
10. Data Science - ⎙

Next Goals

• Adding our university page at Linkedin, so in that way we will be able to add OSS University in our Linkedin profile.

References

• Google - Guide for Technical Development
• Coursera
• edX
• MIT Open Courseware