TIM147: Introduction 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

5 credits

Year	Fall	Winter	Spring	Summer
2025-26		Section 01 Tyler Munger (tmunger)
2024-25			Section 01 Yi Zhang (yiz)
2023-24	Section 01 Yi Zhang (yiz)
2022-23	Section 01 Yi Zhang (yiz)

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