DATA 822 (M1) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Manchester   Coll of Professional Studies :: Analytics
Online Course Delivery Method: Online Asynchronous
Credits: 3.0
Term: Spring 2024 - Term 4 (03/25/2024 - 05/17/2024)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 54092
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DATA 800 and DATA 820 and DATA 821 May be taken concurrently
Mutual Exclusion : ADMN 872
Attributes: Online (no campus visits), EUNH
Instructors: Bogdan Gadidov

Times & Locations

Start Date End Date Days Time Location
3/25/2024 5/17/2024 Hours Arranged ONLINE