Time Series Class - Part 1 - Dr Ioannis Papastathopoulos, University of Edinburgh

This course covers the fundamentals of time series analysis, including moving average, autoregressive, and ARMA models. It also delves into parameter estimation, likelihood-based inference, and forecasting techniques. Advanced topics include state-space models such as hidden Markov models and the Kalman filter, as well as recurrent neural network models. The course teaches skills in estimating autocorrelation, conducting statistical tests, and removing trends from time series data. The teaching method involves lectures and practical applications. This course is intended for individuals interested in gaining a deeper understanding of time series analysis and its applications.