Material from the great IBM MOOC on time series forecasting with python available through Coursera
- Introduction to Time Series Analysis
1.1 Additive, multiplicative and pseudo additive time series
1.2 Decomposition models
- Stationarity and Time Series Smoothing
2.1 Stationarity and Autocorrelation
2.2 Smoothing methods
- ARMA and ARIMA models
3.1 ARMA
3.2 ARIMA and SARIMA
- Deep Learning and Survival Analysis Forecasts
4.1 Deep Learning approach via RNN and LSTM with Keras
4.2 Survival Analysis and Censoring