DESC 624 Predictive Analytics (2)

Students gain critical skills for succeeding in today’s data-intensive world, including business case study, data analysis, and making recommendations to management. They learn how to utilize database systems (SQL and NoSQL) and analytics software built upon R, Python, and SAS. They learn how to make trustworthy predictions using traditional statistics and machine learning methods. Topics include Supervised (prediction and classification) and Unsupervised (exploratory data analysis, principal components, cluster analysis) learning; Prediction models including multiple linear regression, artificial neural networks, regression trees, K-nearest Neighbors; Classification models including logit/probit models and classification trees.

Grading Basis: Graded