Course Course Summary Section 1 Content Section 1 Content Left Section 1 Content Right Credit Type: Course ACE ID: STAT-0024 Organization's ID: 603 Organization: Statistics.com Location: Online Length: 4 weeks Dates Offered: 10/1/2024 - 9/30/2027 6/1/2021 - 9/30/2024 4/1/2018 - 5/31/2021 12/1/2014 - 3/31/2018 Credit Recommendation & Competencies Section 2 Content Section 2 Content Left Section 2 Content Right Level Credits (SH) Subject Upper-Division Baccalaureate 3 Predictive Modelling Description Section 3 Content Section 3 Content Left Section 3 Content Right Objective: The course objective is to cover key unsupervised learning techniques: association rules, principal components analysis, and clustering. Predictive Analytics 3 will include an integration of supervised and unsupervised learning techniques. Learning Outcomes: Understand the issues related to using too many predictors (the “curse of dimensionality”) Combine unsupervised and supervised learning methods in a final project Use association rules to find patterns of “what goes with what” in transaction data Use principal components analysis to reduce the number of predictors to a smaller number of “components” of correlated predictors Use hierarchical clustering and k-means clustering to find and describe clusters of similar records General Topics: Dimension Reduction Cluster Analysis Association Rules and Recommender Systems Integrating Supervised and Unsupervised Methods Introduction to Network and Text Analytics Instruction & Assessment Section 4 Content Section 4 Content Left Section 4 Content Right Instructional Strategies: Discussion Lectures Practical Exercises Textbook readings Methods of Assessment: Other Graded practical exercises and discussion forums Minimum Passing Score: 73% Supplemental Materials Section 5 Content Section 5 Content Left Section 5 Content Right Section 6 Content Section 6 Content Left Section 6 Content Right Button Content Rail Content 1 Other offerings from Statistics.com Biostatistics for Credit (STAT-0002) Calculus Review (STAT-0038) Categorical Data Analysis (STAT-0006) Customer Analytics in R (STAT-0031) Customer Analytics in R with Capstone (STAT-0053) Forecasting Analytics (STAT-0021) Forecasting Analytics with Capstone (STAT-0051) Integer & Nonlinear Programming and Network Flow (STAT-0019) Integer & Nonlinear Programming and Network Flow with Capstone (STAT-0050) Interactive Data Visualization (STAT-0028) View All Courses Page Content