Graduate Course Descriptions

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.

5410. Statistical Computing for Data Science

3.00 credits

Prerequisites: Open to graduate students in the MS in Data Science program, others with permission. Introductory course in mathematical and applied statistics; introductory course in programming.

Grading Basis: Graded

Principles and practice of statistical computing in data science: data structure, distributed computing and project management tools, data visualization, and data programming including simulation, resampling methods, and applications of optimization for statistical modeling, inference, and prediction. Formerly offered as STAT 5125.


Last Refreshed: 20-JUN-24 05.20.07.060883 AM
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Term Class Number Campus Instruction Mode Instructor Section Session Schedule Enrollment Location Credits Grading Basis Notes
Fall 2024 8784 Storrs Online Asynchronous Spencer, Neil 001 Reg 11/45 No Room Required - Online 3.00 Graded