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  1. 0.0.0 About this Wiki
  2. 1.1.1 Definition and Scope
  3. 1.1.2 Problem-Solving Focus
  4. 1.1.3 Interdisciplinary Nature
  5. 1.2.1 Early Calculating Devices (Abacus, Pascaline, Leibniz Wheel)
  6. 1.2.2 Analytical Engine (Babbage & Lovelace)
  7. 1.2.3 Alan Turing: The Brilliant Mind Who Shaped Our Digital World
  8. 1.2.3 Early Electronic Computers (ENIAC, UNIVAC)
  9. 1.2.5 Transistors & Integrated Circuits
  10. 1.2.6 Personal Computers & the Internet
  11. 1.3.1 Ada Lovelace, Alan Turing, Grace Hopper, Dennis Ritchie, Linus Torvalds, etc.
  12. 1.4.1 Theoretical CS, Algorithms, Data Structures, AI, ML, Cybersecurity, Networking, etc.
  13. 1.5 How a Computer Works
  14. 10.0 Artificial Intelligence (AI) & Machine Learning
  15. 10.1.1. Phases (Requirements, Design, Implementation, Testing, Deployment, Maintenance)
  16. 10.1.2 Applications of AI
  17. 10.1 Introduction to AI
  18. 10.1 Software Development Life Cycle (SDLC)
  19. 10.2.1 Supervised Learning (Regression, Classification)
  20. 10.2.2 Unsupervised Learning (Clustering, Dimensionality Reduction)
  21. 10.2.3 Reinforcement Learning
  22. 10.2 Types of Machine Learning
  23. 10.3.1 Linear Regression, Logistic Regression
  24. 10.3.2 Decision Trees, Random Forests
  25. 10.3.3 Support Vector Machines (SVM)
  26. 10.3.4 K-Means Clustering
  27. 10.3 Common ML Algorithms
  28. 10.4.1 Perceptrons, Layers
  29. 10.4.2 Activation Functions
  30. 10.4.3 Backpropagation (High-level)
  31. 10.4.4 Convolutional Neural Networks (CNNs)
  32. 10.4.5 Recurrent Neural Networks (RNNs)
  33. 10.4 Neural Networks & Deep Learning (Basic Concepts)
  34. 10.5.1 Basic tasks and applications
  35. 10.5.2.1 Generative Pre-trained Transformers (GPT)
  36. 10.5.2 Large Language Models (LLMs)
  37. 10.5 Natural Language Processing (NLP) / Computer Vision (CV)
  38. 13.5 Ethical AI & Societal Impact
  39. 16.61 Harvard CS50 (2023) Full Computer Science University Course
  40. 2.1.1 Binary Numbers (Bits, Bytes)
  41. 2.1.2 Number Systems (Decimal, Binary, Octal, Hexadecimal)
  42. 2.1.3 Character Encoding (ASCII, Unicode, UTF-8)
  43. 2.1.4 Image, Audio, and Video Representation (Basic)
  44. 2.2.1 AND, OR, NOT, XOR, NAND, NOR gates
  45. 2.2.2 Truth Tables
  46. 2.2.3 Boolean Expressions & Simplification
  47. 2.3.1 Definition of an Algorithm
  48. 2.3.2 Characteristics of Good Algorithms
  49. 2.3.3 Representing Algorithms (Flowcharts, Pseudocode)
  50. 2.4.1 Decomposition

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