- Module 1: Getting Started with Tensorflow 2 -- Sequential API, validation,regularization, callbacks, early stoppinga and patience, saving and loading model weights, saving and loading architecture, and loading pre-trained models
- Module 2: Customization Your Models with Tensorflow 2 -- Functional API, Data Pipeline, Sequence Modelling - RNNs, Stacked, Bidirectional, stateful, model subclassing, and custom training loops
- Module 3: Probabilistic Deep Learning with Tensorflow 2 -- Probabilistic layers, Bayesian Neural Networks, Bayesian CNN, Bijectors and normalising flows, Variational AutoEncoder, KL Divergence