Introduction to Time Series Analysis, Online teaching

Core content

• Reduction of measurement noise in time series (eg average / weighted average), different filtering options
• Understanding   the concept of internal dependencies (correlation) of the time series,   understanding the dependencies between several types of measurements
• Change rate (differential) and automatic phenomena extraction from data and isolation of significant data from data
• Prediction of data by linear correlation, estimation of missing data

Complementary content

• Visualization of the phenomena both in time and frequency domains
• Implementation of correlation search between the measurement sets.
• Understand how phenomena can be searched automatically

Special knowledge

• Understanding the Dependence Between Time and Frequency Domains
• Knowing another prediction models and have ability to use them

Moodle

General scale, 0-5