Hands-on Deep Learning

Schedule

SES #	Topics	Key Dates
1	Introduction to neural networks and deep learning (motivation, smart representations, layers, activations, architectures); training deep NNs (loss functions, gradient descent, regularization)
2	Training deep NNs (continued); introduction to Keras/Tensorflow (tensors, functional API, training, evaluation); application to tabular data
3	Deep learning for computer vision—building convolutional neural networks from scratch	HW assignment #1 posted
4	Deep learning for computer vision—transfer learning and fine-tuning; introduction to HuggingFace
5	Deep learning for natural language—the basics (tokenization, n-grams, bag-of-words)	HW assignment #1 due
6	Deep learning for natural language—embeddings	HW assignment #2 posted
7	Deep learning for natural language—transformers	Project proposal due
8	Deep learning for natural language—transformers, self-supervised learning
9	Generative AI—large language models (LLMs) and retrieval augmented generation (RAG)	HW assignment #2 due
10	Generative AI—adapting LLMs with parameter-efficient fine-tuning
11	Generative AI—text-to-image models	Projects due
12	Project presentations