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Description

Official Description

8.0 Continuing Education Units (CEUs)

Introduction to the fundamentals of applying artificial intelligence (AI) techniques to time series data. Exploration of statistical, machine learning, and deep learning models, focusing on key applications: forecasting, clustering, and anomaly detection. Topics include: data science methods for time series, including rolling predictions, online learning, and backtesting, with emphasis on deep learning approaches.

Supplementary Information

20 hours of lectures and 60 hours of independent study. Course may be offered in person or online with synchronous and asynchronous activities. The passing grade for this course and the prerequisites courses is B-.

RESTRICTION: Not open to students who have taken YCNG 233 - Time Series Analysis Fundamentals.

Prerequisite(s) and Corequisite(s)

Applies Towards the Following Programs

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