Lecture 1 - Intro & Word Vectors

Lecture 2 - Neural Classifiers

Lecture 3 - Backpropagation and Neural Networks

Lecture 4 - Syntactic Structure and Dependency Parsing

Lecture 5 - Recurrent Neural Networks (RNNs)

Lecture 6 - Simple and LSTM RNNs

Lecture 7 - Translation, Seq2Seq, Attention

Lecture 8 - Self-Attention and Transformers

Lecture 9 - Pretraining

Lecture 10 - Prompting, Reinforcement Learning from Human Feedback

Lecture 11 - Natural Language Generation

Lecture 12 - Question Answering

Lecture 13 - Coreference Resolution

Lecture 14 - Insights between NLP and Linguistics

Lecture 15 - Add Knowledge to Language Models

Lectrue 15 - Code Generation

Lecture 16 - Multimodal Deep Learning, Douwe Kiela