- Introduction to deep learning.
- Fundamentals of Deep Neural Networks (DNNs).
- The art of training DNNs.
- Fundamentals for image analysis using DNNs.
- Convolutional Neural Networks (CNNs).
- Network visualization, image classification and object detection.
- Fully Convolutional Neural networks (FCNs) and image segmentation.
- Fundamentals for text analysis.
- Recurrent Neural Networks (RNNs), attention and transformers.
- Applications in text analysis and image classification with transformers.
The lectures are complemented with hands-on activities using jupyter notebooks.
