DATA 822 (M1) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Manchester   Graduate School :: Analytics
Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - E-term II (10/18/2021 - 12/14/2021)
Grade Mode: Letter Grading
Class Size:   16  
CRN: 16967
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.
Mutual Exclusion : ADMN 872
Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT
Instructors: Bogdan Gadidov

Times & Locations

Start Date End Date Days Time Location
10/18/2021 12/14/2021 Hours Arranged ONLINE