DATA375
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DATA375 - Introduction to Statistical Computing
Course Description
Basic computing skills including random variable generation, Monte Carlo integration, visualization, optimization techniques, re-sampling methods, Bayesian approaches, and introduction to statistical computing environments (R and Python). Material will provide hands-on experience with real world problems. It is expected that students have prior experience in a programming language, preferably Python.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Undergraduate
Enrollment Requirements
017805
Name
Lecture
Workload Hours
3
Optional Component
No
Typically Offered Main Campus
Fall, Spring
Typically Offered Distance Campus
Fall
Typically Offered UA Online Campus
Not Offered
Typically Offered Phoenix Campus
Not Offered
Typically Offered South Campus
Not Offered
Typically Offered Community Campus
Not Offered