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Path to a free self-taught education in Computer Science!
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README.md Reorder courses 2015-05-26 18:23:26 -03:00

README.md

Science

References

Topics

Computer Science

  1. Introduction to Computer Science and Programming - ⎙
  2. Computer Science 101 - Stanford / Other files - ⎙
  3. Fundamentals of Computing
    1. An Introduction to Interactive Programming in Python (Part 1) - ⎙
    2. An Introduction to Interactive Programming in Python (Part 2) - ⎙
    3. Principles of Computing (Part 1) - ⎙
    4. Principles of Computing (Part 2) - ⎙
    5. Algorithmic Thinking (Part 1) - ⎙
    6. Algorithmic Thinking (Part 2) - ⎙
  4. Structure and Interpretation of Computer Programs - ⎙
  5. Elements of Software Construction - ⎙
  6. Introduction to Algorithms - ⎙
  7. Design and Analysis of Algorithms - ⎙
  8. Computer System Engineering - ⎙
  9. Computer Language Engineering - ⎙
  10. Great Ideas in Theoretical Computer Science - ⎙
  11. Performance Engineering of Software Systems - ⎙
  12. Engineering Innovation and Design - ⎙
  13. Principles of Computer System Design: An Introduction - ⎙
  14. How to Process, Analyze and Visualize Data - ⎙
  15. Advanced Data Structures - ⎙
  16. Advanced Algorithms - ⎙
  17. Distributed Algorithms - ⎙

Software Testing

  1. Software Testing - ⎙
  2. Software Debugging - ⎙

Math

  1. Mathematics for Computer Science - ⎙
  2. Introduction to Logic - ⎙
  3. Linear Algebra - ⎙
  4. Coding the Matrix: Linear Algebra through Computer Science Applications - ⎙
  5. Calculus One - ⎙
  6. Calculus Two - ⎙
  7. Linear and Discrete Optimization - ⎙
  8. Probabilistic Graphical Models - ⎙
  9. Game Theory - ⎙
  10. Statistics One - ⎙
  11. AP Statistics - ⎙

Operating Systems

  1. Operating System Engineering - ⎙
  2. Operating Systems and System Programming - ⎙

Networks

  1. Networks - ⎙
  2. Network and Computer Security - ⎙
  3. Network Optimization - ⎙

Databases

  1. Database Systems - ⎙
  2. Database, Internet, and Systems Integration Technologies - ⎙

Cryptography

  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 - ⎙

Robotics

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. Automata, Computability, and Complexity - ⎙
  2. Computational Biology: Genomes, Networks, Evolution - ⎙
  3. Creating Video Games - ⎙
  4. Computer Graphics - ⎙
  5. User Interface Design and Implementation - ⎙
  6. Making Sense of Data - ⎙
  7. Data Science - ⎙