ATNLP: Advanced Topics in Natural Language Processing

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Welcome

The Advanced Topics in Natural Language Processing is a new 20-credit course that covers a set of topics from the modern era of NLP, with a focus on large language models (LLMs). We will soon add "course materials" to the navigation bar to show what topics are covered. The structure of the course is such that each week two lectures are given about the core material, and one lecture is given by an additional staff member in NLP who will discuss their work.

Disclaimer: The choice of topics we cover in this class may seem eclectic at first, and in many ways, it is. In recent years, the field of natural language processing has spawned numerous subareas that have become fertile ground for research and work, which can sometimes be considered fields in their own right. This expansion is especially noticeable, as NLP is now also often identified more generally with artificial intelligence. To put it simply, NLP is now a vast field.

In our choice of "advanced topics", we tried to (a) keep the topics appropriate for all, given the diversity of student backgrounds in the course; (b) keep the topics as "foundational", "representative" and "durable" as possible (to predict), so they can indeed serve better as a scaffold for students who are interested in working in the area in the future; (c) keep the topics at a level that indeed requires guidance and conceptual understanding that are better delivered in lectures rather than self-learning (though self-learning is *highly* encouraged throughout the course).

With that being said, we are open to discussing any other topics during office hours with students, or connecting them to lectures through questions or enquiries during the lectures.

Lecturers: Lexi Birch, Shay Cohen, and Alessandro Suglia

More information will be added when the course is about to start.

Note that ANLP (or equivalent) is a prerequisite to take this course.