TIM 147Introduction to Data Mining for Business
Introduces concepts, approaches, tools, methods for extracting useful knowledge and business value from data for business applications. Covers predictive models, descriptive models, model fitting, model overfitting, complexity, visualization, text mining, association mining, analytical thinking. Other topics may include social network mining, data science and business strategy. Students cannot receive credit for this course and CSE 145.
Prerequisite(s): CSE 30; and MATH 22 or MATH 23A or AM 30; and STAT 5, or STAT 7 and 7L, or STAT 17 and STAT 17L, or STAT 131, or CSE 107.
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When it runs
Winter 2026Open Winter 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 9:50am–11:25am | J Baskin Engr 156 | T. R. Munger | Open 34/35 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Tyler Munger | 5.0 / 5 | 2.6 / 5 | 100% | 14 |
From RateMyProfessors, which is student-submitted and not a survey. Small review counts move a long way on one bad quarter.
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