The MS (DS) program has been designed to give students the option to be part of a data science endeavor that begins with the identification of business processes, determination of data provenance and data ownership, understanding the ecosystem of the business decisions, skill sets and tools that shape the data, making data amenable to analytics, identifying sub-problems, recognizing the technology matrix required for problem resolution, creating incrementally-complex datadriven models and then maintaining them to ultimately leverage them for business growth.
| Course Code | Course Name | Credit Hours | Pre Req |
|---|---|---|---|
| DS603 | Tools and Techniques for Data Science | 3+0 | None |
| CS6XX | Elective-I | 3+0 | None |
| DS602 | Statistical and Mathematical Methods for Data Analysis | 3+0 | None |
| Course Code | Course Name | Credit Hours | Pre Req |
|---|---|---|---|
| CSC501 | Machine Learning | 3+0 | None |
| CS60XX | Specialization-Elective-I | 3+0 | |
| CS60XX | Specialization-Elective-II | 3+0 | |
| Course Code | Course Name | Credit Hours | Pre Req |
|---|---|---|---|
| CS6XX | Elective-II | 3+0 | None |
| DS689 | Thesis-I | 3+0 | None |
| Course Code | Course Name | Credit Hours | Pre Req |
|---|---|---|---|
| CS5XX | Elective-III | 3+0 | None |
| DS699 | Thesis-II | 3+0 | None |
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Lecturer
Lecturer
Lecturer
Lecturer
Lecturer
Lecturer
Junior Lecturer
Junior Lecturer