COMPSCI 685: Advanced Natural Language Processing (Grade: A)

Course Overview:
Natural Language Processing (NLP) is both an engineering art and a science, focused on teaching computers to understand human language. As a subset of artificial intelligence, NLP has become ubiquitous, powering voice assistants, web-based question answering, discussion analysis in social media, and even human language translation. The complexity of language—rich in nuances and ambiguity—makes it challenging for computers to understand, but through the application of data, mathematics, and linguistic insights, these engineering problems can be tackled.

Course Content:
This course provided a deep dive into the latest deep learning methods for NLP, with a strong focus on large language models. Throughout the semester, we concentrated on neural language models and transfer learning techniques that have significantly advanced the state of the art in NLP.

Designed for graduate students in computer science and linguistics, the course targeted those interested in cutting-edge research in NLP and those familiar with machine learning fundamentals. The curriculum covered key areas including:

• Modeling Architectures: Understanding the structure and components of advanced NLP models.
• Training Objectives: Exploring various objectives to optimize model performance.
• Downstream Tasks: Application of NLP techniques in tasks such as text classification, question answering, and text generation.

Coursework:
The course involved engaging with recent research papers, completing challenging programming assignments, and culminating in a final project. The blend of theory and practical application provided a comprehensive understanding of modern NLP techniques.

Achievements:
I successfully completed this course with an A Grade, reflecting my deep understanding and capability in the field of NLP.

Additional Notes:
While the course was held in person, all lectures were livestreamed on YouTube, with video links accessible through the course schedule, ensuring flexibility and access to the material.