This course provides Airmen an introduction and detailed look at the specific realm of data research known as statistical learning. Students will understand supervised and unsupervised learning, when to use linear regression or classification regression. Additionally resampling methods and model validations are discussed and implemented. The regularization of model selection through subset, dimensional reduction and ridge regression are examined. Finally, Tableau visualizations are implemented upon the statistical learning results to tell a story to the decision makers and stock holders. This is an advanced course in data research for students familiar with statistical theory and modeling methods. Additionally students should have experience with R-studio.
Grade Restrictions: None
Special Requirements: None
Delivery Method: e-Learning Course
Course Length:Event Type: Training (Functional, Technical)
CL Points: 30