Data Mining & Pred Modeling
Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2022 - E-term IV (03/21/2022 - 05/12/2022)
Grade Mode: Letter Grading
Term: Spring 2022 - E-term IV (03/21/2022 - 05/12/2022)
Grade Mode: Letter Grading
Class Size:
30
CRN: 53042
CRN: 53042
In this class, students will learn foundations of practical machine learning: upon completion, students will be able to understand and apply supervised and unsupervised learning in Python to build predictive models on real world datasets. Techniques covered include (but not limited to): preprocessing, dimensionality reduction, clustering, feature engineering and model evaluation. Models covered include: generalized linear models, tree-based models, bayesian models, support vector machines, and neural networks. All learning objectives are achieved through active application of these techniques to real world datasets. Prereq: DATA 800; DATA 820 Pre- or Coreq: DATA 821.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Mutual Exclusion : ADMN 872
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Bogdan Gadidov
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
3/21/2022 | 5/12/2022 | Hours Arranged | ONLINE |