Path to a free self-taught education in Computer Science!

• Summary
• Curriculum

This is a visualization of my personal learning goals and progress. My curriculum doesn't exactly match the OSSU curriculum as I've streamlined the advanced topics and omitted some foundational ones I'm already confident in.

• Intro CS
  • Introduction to Computer Science
• Core CS
  • Core programming
  • Core math
  • Core systems
  • Core theory
  • Core security
  • Core applications
• Advanced CS
  • Advanced programming
  • Advanced systems
  • Advanced theory
  • Advanced information security
  • Advanced math
• Final project

An entry-level course taught by David J. Malan, CS50x teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML

Topics covered: computation imperative programming basic data structures and algorithms and more

All coursework under Core CS is required, unless otherwise indicated.

Topics covered: design for testing program requirements common design patterns unit testing object-oriented design static typing

Discrete math (Math for CS) is a prerequisite and closely related to the study of algorithms and data structures.

Topics covered: discrete mathematics mathematical proofs basic statistics O-notation discrete probability and more

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

Topics covered: procedural programming manual memory management boolean algebra gate logic memory computer architecture assembly machine language virtual machines high-level languages compilers operating systems network protocols and more

Topics covered: divide and conquer sorting and searching randomized algorithms graph search shortest paths data structures greedy algorithms minimum spanning trees dynamic programming NP-completeness and more

Topics covered Confidentiality, Integrity, Availability Secure Design Defensive Programming Threats and Attacks Network Security Cryptography and more

Topics covered: Agile methodology REST software specifications refactoring relational databases transaction processing data modeling neural networks supervised learning unsupervised learning OpenGL ray tracing and more

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.

Topics covered: debugging theory and practice goal-oriented programming parallel computing object-oriented analysis and design UML large-scale software architecture and design and more

(*) book by Blackburn, Bos, Striegnitz (compiled from source, redistributed under CC license)

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

Topics covered: formal languages Turing machines computability event-driven concurrency automata distributed shared memory consensus algorithms state machine replication computational geometry theory propositional logic relational logic Herbrand logic game trees and more

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• Eric Douglas: founder of OSSU
• Josh Hanson: lead technical maintainer
• Waciuma Wanjohi: lead academic maintainer
• Contributors