Advances in AI and NLP

Advances in AI and NLP#

Course Description:#

This course provides an in-depth exploration of recent advances in artificial intelligence and natural language processing, with a focus on influential research papers published after 2016. Students will read and analyze seminal papers on topics such as neural networks, sequence modeling, generative models, and natural language processing. The course will emphasize critical reading and thinking skills, as well as practical implementation skills, through a series of presentations and discussion sessions.

Learning Objectives:#

Upon completing this course, students will be able to:

  • Understand and critique the main concepts, techniques, and architectures in artificial intelligence and natural language processing.

  • Analyze and apply the latest research in artificial intelligence and natural language processing to real-world problems.

  • Develop strong written and oral communication skills through presentations and group discussions.

Prerequisites:#

  • Familiarity with programming (preferably Python)

  • Basic knowledge of machine learning and deep learning

  • Basic knowledge of natural language processing

Grading:#

  • Class participation and attendance: 20%

  • Presentations and group discussions: 30%

  • Final project: 50%

Table of Contents#

Contents