Program: MSIS/PhD
Course Areas
General Information Studies Elective
Data Science/Engineering/Analytics
Catalog Description
Foundational data science-related techniques and their essential mathematical and computational background.
Instructor Description
This class explores various data science models, both traditional and the state of the art techniques. The course is designed to provide mathematical and computational basis such as Linear Algebra, Optimization techniques, and probabilistic modeling for different types of machine learning models. The goal of the class is provide a foundational basis for data science techniques. The class focuses on PSETs and a final data science project.
Prerequisites
Graduate standing.
Restrictions
Enrollment in Information Studies (INF) courses is restricted to graduate students in the School of Information through registration periods 1 and 2, with outside students only being accepted during period 3.
Current and Upcoming Classes for this Course
| Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
|---|---|---|---|---|---|---|
| INF 385T: Special Topics in Information Science: Foundations of Data Science
Shounak Roychowdhury Syllabus |
Fall Term 2025 |
|
|
|
|
|
Past Classes for this Course
| Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
|---|---|---|---|---|---|---|
| INF 385T: Special Topics in Information Science: Foundations of Data Science
Shounak Roychowdhury Syllabus |
Fall Term 2024 |
|
|
|
|
|