ISTA331
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ISTA331 - Principles and Practice of Data Science
Course Description
ISTA 331 explores the ideas and techniques that businesspersons and scientists alike use to exploit data in order to create knowledge and make money. Topics and projects may include recommender systems (which powered Amazon's rise to global retail dominance), spam filters (the first machine learning application that affected our daily lives), topic extraction from documents, and an introduction to neural networks.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Undergraduate
Enrollment Requirements
017518
May be convened with
Name
Discussion
Workload Hours
1
Optional Component
No
Name
Lecture
Workload Hours
2
Optional Component
No
Typically Offered Main Campus
Fall (even years only)