Deep learning curriculum for robotics. [📍 Link to Playlist below ] Modern robotics workflows often integrate deep learning models with traditional algorithms for mapping, localization, and control. This playlist builds it from scratch: Single neurons → Backprop → CNNs → Transformers → GANs → AlphaGo. Step by step. Taught by Prof. Bryce, one of the clearest educators in the field. 26 lectures covering: → CNNs (robotic vision & object detection) → Transformers (planning & foundation models)→ LSTMs/RNNs (sequential decision-making) → GANs (synthetic training data) → AlphaGo (reinforcement learning for robot control) If you’re building robots or trying to understand how they learn, this is the foundation. 📍