Learning Time Series with Interventions

An in-depth introduction to time series analysis, from learning structured models to predictions and reinforcement learning, with hands-on projects - Part of the MITx MicroMasters program in Statistics and Data Science.

Syllabus

Analyze time series through the perspective of Linear Time-invariant (LTI) systems and use methods and tools such as spectral analysis.
Model time series using autoregressive moving average (ARMA) and integrated processes.
Perform prediction, imputation on general time series data using matrix completion methods.
Use various dynamical programming and reinforcement learning algorithms to optimize control and interventions for time series.