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Creating Features for Time Series Data

By Coursera on Coursera · Data Science
Price
Free

About This Course

This course focuses on data exploration, feature creation, and feature selection for time sequences. The topics discussed include binning, smoothing, transformations, and data set operations for time series, spectral analysis, singular spectrum analysis, distance measures, and motif analysis. In this course you learn to perform motif analysis and implement analyses in the spectral or frequency domain. You also discover how distance measures work, implement applications, explore signal components, and create time series features. This course is appropriate for analysts with a quantitative background as well as domain experts who would like to augment their time-series tool box. Before taking this course, you should be comfortable with basic statistical concepts. You can gain this experience by completing the Statistics with SAS course. Familiarity with matrices and principal component analysis are also helpful but not required.

Instructor

Chip Wells

Frequently Asked Questions

How much does Creating Features for Time Series Data cost?
Visit the Creating Features for Time Series Data course page for current pricing and available discounts.
Who teaches Creating Features for Time Series Data?
Creating Features for Time Series Data is taught by Chip Wells, SAS.
What skill level is Creating Features for Time Series Data for?
This course is designed for all levels learners.