AI TRACK

Artificial Intelligence & Deep Learning Masterclass

Python, Linear Algebra, PyTorch, Convolutional Nets, Transformers, and LLM Fine-Tuning.

Progress

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  1. MODULE 1

    Module 1: Foundations of Deep Learning & Tensors

    3 Hours

    Topics Covered:

    • PyTorch Autograd
    • Activation Functions
    • Loss Functions
    • Gradient Descent
    Deep learning models learn feature hierarchies automatically through backpropagation and automatic differentiation.

  2. MODULE 2

    Module 2: Transformers & Attention Mechanism

    5 Hours

    Topics Covered:

    • Self-Attention
    • Multi-Head Attention
    • Positional Encoding
    • Decoder-only LLMs
    Self-attention computes pairwise query-key similarity matrices to capture contextual relationships across sequences.