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Learning path

AI from Scratch

Implement the math behind modern ML — backprop in a neural network, then a GPT-style transformer. No PyTorch shortcuts.

advanced2 courses39 lessons~10 hoursFree
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Course sequence

  1. 01

    Build a Neural Network

    Not started

    Build an MNIST classifier from scratch in NumPy: neurons, dense layers, sigmoid/ReLU/softmax, MSE/cross-entropy loss, manual backpropagation, gradient descent + Adam, training loop, and the path to PyTorch/TensorFlow.

    advanced25 lessons~6h
  2. 02

    Build a Transformer (GPT-style)

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    Build a tiny GPT in NumPy: token + position embeddings, layer normalization, scaled dot-product self-attention, multi-head attention with causal mask, feed-forward networks, residual connections, sampling (greedy, top-k, top-p), and the architecture behind ChatGPT, Claude, Llama.

    advanced14 lessons~4h

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AI from Scratch