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Course Guide for learning Artifical Intelligence and Machine Learning

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  • fianio
    Member
    • Jul 2024
    • 1

    #1

    Course Guide for learning Artifical Intelligence and Machine Learning

    Hello everyone,
    I had been always the great fan of defcon and the technology you guys have introduced. Today i would like to ask for the Complete Syllabus to study for AI and ML.
    Can any one help me with this?
  • eren
    Member
    • Aug 2025
    • 1

    #2
    Hello there !
    To start AI and ML you need to get started in theses areas :
    (optional this is first but will be of great use while understanding concepts in detail or even for small things)
    • 1.Probability and Statistics
    • 2.Linear Algebra
    • 3.Calculus (Basics only)

    next up are basic terminologies like
    Types of ML
    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning
    • ML Pipeline Overview:
      • Data collection, cleaning, preprocessing
      • Model training, evaluation, deployment
    next up is learning them and applying them in deep understanding:
    1. Neural Networks Basics
    2. Perceptron
    3. Activation Functions (Sigmoid, ReLU, Tanh)
    4. Loss Functions
    5. Backpropagation
    6. Gradient Descent
    7. Deep Learning Frameworks
    8. Introduction to TensorFlow & PyTorch (Choose one)
    9. Deep Neural Networks
    10. Feedforward Neural Networks
    11. Convolutional Neural Networks (CNNs)
    12. Recurrent Neural Networks (RNNs)
    13. LSTMs (intro only)
    finally try making real useful projects these may be difficult but will be very useful in the future

    After completion of these basic projects pick one or two specializations like
    1. computer vision
    2. nlp/llms
    3. LLMs + GenAI
    4. Applied ML

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