Advanced undergraduate course in Natural Language Processing, covering topics from classic unigram methods to most advanced large pretrained language models, instruction finetuning and alignment.

Syllabus

Natural Language Processing (NLP) aims to develop methods for processing, analyzing and understanding natural language. The goal of this class is to provide a thorough overview of modern methods in the field of Natural Language Processing. The class will not assume prior knowledge in NLP. Among others, we will cover word representations, language modeling, sequence models, and self-supervision, focusing on the interface between structured prediction and deep learning. Course website