The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.
5255. Introduction to Data Science
3.00 credits
Prerequisites: Open to graduate students in Statistics, others with permission. Not open for credit to students who have passed STAT 3255. Recommended preparation: STAT 1000Q or 1100Q or 5005 or equivalent; STAT 2255 or equivalent; and STAT 3115Q or equivalent.
Grading Basis: Graded
Introduction to data science for effectively storing, processing, visualizing, analyzing and making inferences from data to enable decision making. Topics include project management, data preparation, data visualization, statistical modeling, machine learning, distributed computing and ethics.
Last Refreshed: 29-MAR-24 05.20.11.748914 AM
Term | Class Number | Campus | Instruction Mode | Instructor | Section | Session | Schedule | Enrollment | Location | Credits | Grading Basis | Notes | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1243 5890 1 001 | Spring 2024 | 5890 | Storrs | In Person | Yan, Jun Mcclurg-Wong, Taelor |
001 | Reg | MoWe 2:30pm‑3:45pm |
1/5 | AUST 313 | 3.00 | Graded | |
1248 8788 1 001 | Fall 2024 | 8788 | Storrs | In Person | Yan, Jun | 001 | Reg | MoWe 1:25pm‑2:40pm |
0/5 | AUST 445 | 3.00 | Graded |