1. Course Introduction
2. First Approaches for Image Classification
3. Loss Functions and Optimization
4. Neural Networks Basics & Backpropagation
5. Convolutional Neural Networks
6. Training Neural Networks
7. Transfer Learning, CNN Case Studies
8. Object Detection
9. Video Classification (Action Recognition)
10. Recurrent Neural Networks
11. RNN-based Video Models
12. Metric Learning
13. Multimodal Learning
14. Generative Models
15. Self-supervised Learning
16. Style Transfer
17. Scientific Applications