Summary
The OSSU curriculum is a complete education in computer science using online materials. It’s not merely for career training or professional development. It’s for those who want a proper, wellrounded grounding in concepts fundamental to all computing disciplines, and for those who have the discipline, will, and (most importantly!) good habits to obtain this education largely on their own, but with support from a worldwide community of fellow learners.
It is designed according to the degree requirements of undergraduate computer science majors, minus general education (nonCS) requirements, as it is assumed most of the people following this curriculum are already educated outside the field of CS. The courses themselves are among the very best in the world, often coming from Harvard, Princeton, MIT, etc., but specifically chosen to meet the following criteria.
Courses must :
 Be open for enrollment
 Run regularly (ideally in selfpaced format, otherwise running multiple times per year)
 Be of generally high quality in teaching materials and pedagogical principles
 Match the curricular standards of the CS 2013: Curriculum Guidelines for Undergraduate Degree Programs in Computer Science
When no course meets the above criteria, the coursework is supplemented with a book. When there are courses or books that don’t fit into the curriculum but are otherwise of high quality, they belong in extras/courses or extras/readings.
Organization . The curriculum is designed as follows:
 Intro CS : for students to try out CS and see if it’s right for them
 Core CS : corresponds roughly to the first three years of a computer science curriculum, taking classes that all majors would be required to take
 Advanced CS : corresponds roughly to the final year of a computer science curriculum, taking electives according to the student’s interests
 Final Project : a project for students to validate, consolidate, and display their knowledge, to be evaluated by their peers worldwide
Duration . It is possible to finish Core CS within about 2 years if you plan carefully and devote roughly 1822 hours/week to your studies. Courses in Core CS should be taken linearly if possible, but since a perfectly linear progression is rarely possible, each class’s prerequisites are specified so that you can design a logical but nonlinear progression based on the class schedules and your own life plans.
Cost . All or nearly all course material is available for free. However, some courses may charge money for assignments/tests/projects to be graded. Note that Coursera offers financial aid.
Decide how much or how little to spend based on your own time and budget; just remember that you can’t purchase success!
Process . Students can work through the curriculum alone or in groups, in order or out of order.
 For grouping up, please use the cohorts repository to find or create a cohort suited to you.
 We recommend doing all courses in Core CS, only skipping a course when you are certain that you’ve already learned the material previously.
 For simplicity, we recommend working through courses (especially Core CS) in order from top to bottom, as they have already been topologically sorted by their prerequisites.
 Courses in Advanced CS are electives. Choose one subject (e.g. Advanced programming) you want to become an expert in and take all the courses under that heading. You can also create your own custom subject, but we recommend getting validation from the community on the subject you choose.
Content policy . If you plan on showing off some of your coursework publicly, you must share only files that you are allowed to. Do NOT disrespect the code of conduct that you signed in the beginning of each course!
Curriculum
 Prerequisites
 Intro CS
 Introduction to Programming
 Introduction to Computer Science
*Introduction to CS Tools
 Core CS
 Core programming
 Core math
 Core systems
 Core theory
 Core applications
 Core security
 Advanced CS
 Advanced programming
 Advanced systems
 Advanced theory
 Advanced applications
 Final project
Prerequisites
 Core CS assumes the student has already taken high school math, including algebra, geometry, and precalculus.
 Advanced CS assumes the student has already taken the entirety of Core CS and is knowledgeable enough now to decide which electives to take.
 Note that Advanced systems assumes the student has taken a basic physics course (e.g. AP Physics in high school).
Intro CS
Introduction to Programming
If you’ve never written a forloop, or don’t know what a string is in programming, start here. Choose one of the two course series below. Either one will give you an introduction to programming that assumes no prior knowledge. You can audit either for free, in order to do so, click through to the individual courses in the specializations .
Trying to decide between them?
Python for Everyone will introduce you to a popular language and will quickly move to practical programming tasks  using web APIs and databases. This will give you a taste of what many professional developers do.
Fundamentals of Computing will also start by introducing you to Python. It then moves on to give an introduction to academic Computer Science topics, like sorting and recursion. This will give you a taste of what the following courses will be like. (Students who complete Fundamentals of Computing can skip Intro to Computer Science and begin Introduction to CS Tools.)
Topics covered : simple programs
simple data structures
Courses  Effort  Prerequisites 

Python for Everyone (alt)  58 hours  none 
Fundamentals of Computing  138 hours  high school mathematics 
Introduction to Computer Science
This course will introduce you to the world of computer science. Students who have been introduced to programming, either from the courses above or through study elsewhere, should take this course for a flavor of the material to come. If you finish the course wanting more, Computer Science is likely for you!
Topics covered : computation
imperative programming
basic data structures and algorithms
and more
Courses  Duration  Effort  Prerequisites 

Introduction to Computer Science and Programming using Python (alt)  9 weeks  15 hours/week  high school algebra 
Introduction to CS Tools
Understanding theory is important, but you will also be expected to create programs. There are a number of tools that are widely used to make that process easier. Learn them now to ease your future work writing programs.
Topics covered : terminals and shell scripting
vim
command line environments
version control
and more
Courses  Duration  Effort  Prerequisites 

The Missing Semester of Your CS Education  2 weeks  12 hours/week   
Core CS
All coursework under Core CS is required , unless otherwise indicated.
Core programming
Topics covered : functional programming
design for testing
program requirements
common design patterns
unit testing
objectoriented design
Java
static typing
dynamic typing
MLfamily languages (via Standard ML)
Lispfamily languages (via Racket)
Ruby
and more
The How to Code courses are based on the textbook How to Design Programs. The First Edition is available for free online and includes problem sets and solutions. Students are encouraged to do these assignments.
Courses  Duration  Effort  Prerequisites 

How to Code  Simple Data  7 weeks  810 hours/week  none 
How to Code  Complex Data  6 weeks  810 hours/week  How to Code: Simple Data 
Programming Languages, Part A  5 weeks  48 hours/week  How to Code (Hear instructor) 
Programming Languages, Part B  3 weeks  48 hours/week  Programming Languages, Part A 
Programming Languages, Part C  3 weeks  48 hours/week  Programming Languages, Part B 
Math Electives
Students must choose one of the following topics : calculus, linear algebra, logic, or probability.
Calculus
Courses  Duration  Effort  Prerequisites 

Calculus 1A: Differentiation  13 weeks  610 hours/week  precalculus 
Calculus 1B: Integration  13 weeks  510 hours/week  Calculus 1A 
Calculus 1C: Coordinate Systems & Infinite Series  6 weeks  510 hours/week  Calculus 1B 
Linear Algebra
Courses  Duration  Effort  Prerequisites 

Essence of Linear Algebra      precalculus 
Linear Algebra  14 weeks  12 hours/week  Essence of Linear Algebra 
Logic
Courses  Duration  Effort  Prerequisites 

Introduction to Logic  10 weeks  48 hours/week  set theory 
Probability
Courses  Duration  Effort  Prerequisites 

Introduction to Probability  The Science of Uncertainty  18 weeks  12 hours/week  Multivariable Calculus 
Core Math
In addition to their math elective, students must complete the following course on discrete mathematics.
Topics covered : discrete mathematics
mathematical proofs
basic statistics
Onotation
discrete probability
and more
Courses  Duration  Effort  Notes  Prerequisites 

Mathematics for Computer Science  13 weeks  5 hours/week  An alternate version with solutions to the problem sets is here. Students struggling can consider the Discrete Mathematics Specialization first. It is more interactive but less comprehensive, and costs money to unlock full interactivity.  Calculus 1C 
Core systems
Topics covered : procedural programming
manual memory management
boolean algebra
gate logic
memory
computer architecture
assembly
machine language
virtual machines
highlevel languages
compilers
operating systems
network protocols
and more
Courses  Duration  Effort  Additional Text / Assignments  Prerequisites 

Introduction to Computer Science  CS50 (alt)  12 weeks  1020 hours/week  After the sections on C, skip to the next course. Why?  introductory programming 
Build a Modern Computer from First Principles: From Nand to Tetris (alt)  6 weeks  713 hours/week    Clike programming language 
Build a Modern Computer from First Principles: Nand to Tetris Part II  6 weeks  1218 hours/week    one of these programming languages, From Nand to Tetris Part I 
Introduction to Computer Networking  8 weeks  4–12 hours/week  Assignment 1 
Assignment 2
Assignment 3
Assignment 4algebra, probability, basic CS
Operating Systems: Three Easy Pieces1012 weeks6 hours/weekHomework Lectures Supplementalgorithms
Core theory
Topics covered : divide and conquer
sorting and searching
randomized algorithms
graph search
shortest paths
data structures
greedy algorithms
minimum spanning trees
dynamic programming
NPcompleteness
and more
Courses  Duration  Effort  Prerequisites 

Divide and Conquer, Sorting and Searching, and Randomized Algorithms  4 weeks  48 hours/week  any programming language, Mathematics for Computer Science 
Graph Search, Shortest Paths, and Data Structures  4 weeks  48 hours/week  Divide and Conquer, Sorting and Searching, and Randomized Algorithms 
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming  4 weeks  48 hours/week  Graph Search, Shortest Paths, and Data Structures 
Shortest Paths Revisited, NPComplete Problems and What To Do About Them  4 weeks  48 hours/week  Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming 
Core Security
Topics covered Confidentiality, Integrity, Availability
Secure Design
Defensive Programming
Threats and Attacks
Network Security
Cryptography
and more
Note: These courses are provisionally recommended . There is an open Request For Comment on security course selection. Contributors are encouraged to compare the various courses in the RFC and offer feedback.
Courses  Duration  Effort  Prerequisites 

Information Security: Context and Introduction  5 weeks  3 hours/week   
Principles of Secure Coding  4 weeks  4 hours/week   
Identifying Security Vulnerabilities  4 weeks  4 hours/week   
Choose one of the following:
Courses  Duration  Effort  Prerequisites 

Identifying Security Vulnerabilities in C/C++Programming  4 weeks  5 hours/week   
Exploiting and Securing Vulnerabilities in Java Applications  4 weeks  5 hours/week   
Core applications
Topics covered : Agile methodology
REST
software specifications
refactoring
relational databases
transaction processing
data modeling
neural networks
supervised learning
unsupervised learning
OpenGL
raytracing
and more
Courses  Duration  Effort  Prerequisites 

Relational Database Systems  6 weeks  3 hours/week   
Machine Learning  11 weeks  46 hours/week  linear algebra 
Computer Graphics  6 weeks  12 hours/week  C++ or Java, linear algebra 
Software Engineering: Introduction  6 weeks  810 hours/week  Core Programming, and a sizable project 
Software Development Capstone Project  67 weeks  810 hours/week  Software Engineering: Introduction 
Advanced CS
After completing every required course in Core CS, students should choose a subset of courses from Advanced CS based on interest. Not every course from a subcategory needs to be taken. But students should take every course that is relevant to the field they intend to go into.
The Advanced CS study should then end with one of the Specializations under Advanced applications. A Specialization’s Capstone, if taken, may act as the Final project, if permitted by the Honor Code of the course. If not, or if a student chooses not to take the Capstone, then a separate Final project will need to be done to complete this curriculum.
Advanced programming
Topics covered : debugging theory and practice
goaloriented programming
GPU programming
CUDA
parallel computing
objectoriented analysis and design
UML
largescale software architecture and design
and more
Courses  Duration  Effort  Prerequisites 

Introduction to Parallel Programming (alt) (HW)  12 weeks    C, algorithms 
Compilers (alt)  9 weeks  68 hours/week  none 
Introduction to Haskell  14 weeks     
Learn Prolog Now!  12 weeks     
Software Debugging  8 weeks  6 hours/week  Python, objectoriented programming 
Software Testing  4 weeks  6 hours/week  Python, programming experience 
LAFF  On Programming for Correctness  7 weeks  6 hours/week  linear algebra 
Software Architecture & Design  8 weeks  6 hours/week  software engineering in Java 
Advanced systems
Topics covered : digital signaling
combinational logic
CMOS technologies
sequential logic
finite state machines
processor instruction sets
caches
pipelining
virtualization
parallel processing
virtual memory
synchronization primitives
system call interface
and more
Courses  Duration  Effort  Prerequisites 

Electricity and Magnetism, Part 11  7 weeks  810 hours/week  calculus, basic mechanics 
Electricity and Magnetism, Part 2  7 weeks  810 hours/week  Electricity and Magnetism, Part 1 
Computation Structures 1: Digital Circuits  10 weeks  6 hours/week  electricity, magnetism 
Computation Structures 2: Computer Architecture  10 weeks  6 hours/week  Computation Structures 1 
Computation Structures 3: Computer Organization  10 weeks  6 hours/week  Computation Structures 2 
1 Note : These courses assume knowledge of basic physics. (Why?) If you are struggling, you can find a physics MOOC or utilize the materials from Khan Academy: Khan Academy  Physics
Advanced theory
Topics covered : formal languages
Turing machines
computability
eventdriven concurrency
automata
distributed shared memory
consensus algorithms
state machine replication
computational geometry theory
propositional logic
relational logic
Herbrand logic
concept lattices
game trees
and more
Courses  Duration  Effort  Prerequisites 

Theory of Computation (Lectures)  8 weeks  10 hours/week  discrete mathematics, logic, algorithms 
Computational Geometry  16 weeks  8 hours/week  algorithms, C++ 
Introduction to Formal Concept Analysis  6 weeks  46 hours/week  logic, probability 
Game Theory  8 weeks  3 hours/week  mathematical thinking, probability, calculus 
Advanced applications
These Coursera Specializations all end with a Capstone project. Depending on the course, you may be able to utilize the Capstone as your Final Project for this Computer Science curriculum. Note that doing a Specialization with the Capstone at the end always costs money. So if you don’t wish to spend money or use the Capstone as your Final, it may be possible to take the courses in the Specialization for free by manually searching for them, but not all allow this.
Courses  Duration  Effort  Prerequisites 

Modern Robotics (Specialization)  26 weeks  25 hours/week  freshmanlevel physics, linear algebra, calculus, linear ordinary differential equations 
Data Mining (Specialization)  30 weeks  25 hours/week  machine learning 
Big Data (Specialization)  30 weeks  35 hours/week  none 
Internet of Things (Specialization)  30 weeks  15 hours/week  strong programming 
Cloud Computing (Specialization)  30 weeks  26 hours/week  C++ programming 
Full Stack Web Development (Specialization)  27 weeks  26 hours/week  programming, databases 
Data Science (Specialization)  43 weeks  16 hours/week  none 
Functional Programming in Scala (Specialization)  29 weeks  45 hours/week  One year programming experience 
Game Design and Development (Specialization)  6 months  5 hours/week  programming, interactive design 
Final project
OSS University is projectfocused . 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 realworld problem.
After you’ve gotten through all of Core CS and the parts of Advanced CS relevant to you, you should think about a problem that you can solve using the knowledge you’ve acquired. Not only does real project work look great on a resume, but the project will also validate and consolidate your knowledge. You can create something entirely new, or you can find an existing project that needs help via websites like CodeTriage or First Timers Only.
Another option is using the Capstone project from taking one of the Specializations in Advanced applications; whether or not this makes sense depends on the course, the project, and whether or not the course’s Honor Code permits you to display your work publicly. In some cases, it may not be permitted; do not violate your course’s Honor Code!
Put the OSSUCS badge in the README of your repository!
 Markdown:
[![Open Source Society University  Computer Science](https://img.shields.io/badge/OSSUcomputerscienceblue.svg)](https://github.com/ossu/computerscience)
 HTML:
<a href="https://github.com/ossu/computerscience"><img alt="Open Source Society University  Computer Science" src="https://img.shields.io/badge/OSSUcomputerscienceblue.svg"></a>
Evaluation
Upon completing your final project, submit your project’s information to PROJECTS via a pull request and use our community channels to announce it to your fellow students.
Your peers and mentors from OSSU will then informally evaluate your project. You will not be “graded” in the traditional sense — everyone has their own measurements for what they consider a success. The purpose of the evaluation is to act as your first announcement to the world that you are a computer scientist and to get experience listening to feedback — both positive and negative — and taking it in stride.
The final project evaluation has a second purpose: to evaluate whether OSSU, through its community and curriculum, is successful in its mission to guide independent learners in obtaining a worldclass computer science education.
Cooperative work
You can create this project alone or with other students! We love cooperative work ! Use our channels 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 final project.
The important thing is to internalize the core concepts and to be able to use them with whatever tool (programming language) that you wish.
Congratulations
After completing the requirements of the curriculum above, you will have completed the equivalent of a full bachelor’s degree in Computer Science. Congratulations!
What is next for you? The possibilities are boundless and overlapping:
 Look for a job as a developer!
 Check out the readings for classic books you can read that will sharpen your skills and expand your knowledge.
 Join a local developer meetup (e.g. via meetup.com).
 Pay attention to emerging technologies in the world of software development:
 Explore the actor model through Elixir, a new functional programming language for the web based on the battletested Erlang Virtual Machine!
 Explore borrowing and lifetimes through Rust, a systems language which achieves memory and threadsafety without a garbage collector!
 Explore dependent type systems through Idris, a new Haskellinspired language with unprecedented support for typedriven development.
Code of conduct
How to show your progress
 Create an account in Trello.
 Copy this board to your personal account. See how to copy a board here.
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 Resources
: cards with that label represent courses that were 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 theSection
label are only to help the organization of the Done column. You should put the Course’s cards below its respective Section’s card .
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 .
Team
 Eric Douglas : founder of OSSU
 hanjiexi : lead technical maintainer
 waciumawanjohi : lead academic maintainer
 Contributors
Source : GitHub
For more freebies, Do follow our site : www.freesoff.com
Follow on telegram : https://t.me/freesoff
For any Queries, Reply Below!