Powered by AISKOOL
Deep Learning Foundations
Master the core ideas powering modern AI — from neurons and backprop to CNNs, RNNs, and hands-on PyTorch — through clear explanations and practical exercises that build real intuition fast.
4 sections·12 lessons
What you'll learn
1. Neural Networks from Scratch
- What Is a Neural Network?
- Anatomy of a Neuron
- Activation Functions: Breathing Non-Linearity In
2. Backpropagation and Training
- Loss Functions and the Goal of Training
- Gradient Descent on a Loss Landscape
- Backpropagation: The Engine of Learning
3. Convolutional and Recurrent Networks
- CNNs: Teaching Networks to See
- CNN Feature Extraction Layers
- RNNs and LSTMs: Networks That Remember
4. PyTorch in Practice
- PyTorch Fundamentals: Tensors and Autograd
- Training Loop and Best Practices
- Deep Learning Knowledge Check
Share this course