- Basics of Data Preparation Pipeline
- Introduction to deep learning and neural networks
- Mathematical foundations of deep learning
- Architecture of neural networks
- Training neural networks
- Convolutional Neural Nets (CNNs)
- Recurrent neural networks (RNNs) and LSTM
- Reinforcement Learning (RL)
- Evolutionary algorithms (EA)
- Practical application and frameworks
