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Course Description

This predictive analysis block presents the key concepts, techniques, and code approaches for predictive modeling and visualization analysis. Students will be tasked to discuss, employ, apply, assess, and explain predictive-related topics, such as linear regression, time-series, ETC, ARIMA, and HTC modeling. The block includes an optional forecasting project module to help students understand the differences between forecasting and prediction analytics.

Course Outline

•    Module 1: Introduction to Prediction
•    Module 2: Time-Series and Visualization
•    Module 3: ETS
•    Module 4: ARIMA + HTS models
•    Module 5: Forecasting application project
 

Learner Outcomes

•    Discuss challenges associated with prediction
•    Describe the challenges of prediction
•    Explain R for predictive analytics
•    Formulate Linear Regression models
•    Employ and interpret Time-series models
•    Discuss and analyze ETS models
•    Apply and assess ARIMA + HTS models
 
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