Current Topics in Applied Machine Learning (CPSC 482/582)

Semester: Spring 2024

Course Description:

This course delves into cutting-edge developments in applied machine learning, emphasizing their relevance and application in real-world scenarios. The syllabus explores a broad spectrum of methodologies and how they intersect with various fields, such as finance, healthcare, genomics, protein folding, drug discovery, neuroscience, and natural language processing. Designed as an interactive seminar, the course comprises a mixture of insightful lectures from the instructor, guest lectures from experts in the field, and student-led presentations. Students will be encouraged to critically evaluate and discuss recent peer-reviewed publications from prestigious journals and conferences in machine learning. To culminate the learning experience, a final project will require students to implement a machine learning technique on real-world data, illustrating the practical impact of machine learning methodologies.

List of Topics:

• Core Machine Learning Algorithms

• Advanced Deep Learning Techniques

• Principles of Data Science

• Big Data Analytics

Applications of Machine Learning in:

• Genomics and Computational Biology

• Healthcare Innovations

• Neuroscience Research

• Protein Folding and Drug Discovery

• Financial Modeling and Risk Analysis

• Physical Sciences

• Chemical Informatics