Time Series Analysis using Machine Learning, 5 op

Core content

• Reduction of noise in time series, different filtering options, outlier processing
• Understanding the concept of internal dependencies (correlation) of the time series, understanding the dependencies between several types of measurements
  
• Automatic phenomena extraction from data and isolation of significant data from time series
• Feature extraction from time series
  
• Prediction of data by using linear and machine learning methods, 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
• Model selection
  

Special knowledge

• Understanding the Dependence Between Time and Frequency Domains
• Good knowledge of machine learning models, finetuning