Time Series Forecasting Udacity

Overview

About the course

• Learn the fundamentals of time series forecasting and develop proficiency in ETS and ARIMA models, two the most commonly used models in forecasting with our Time Series Forecasting course from Udacity.

What you will learn

• you’ll learn what attributes make data a time series. You’ll also learn the key components used in time series forecasting, such as seasonality, trends, and cyclical patterns.
• you’ll learn how to build and use ETS models. ETS stands for error, trend, and seasonality, and are the three inputs in ETS models. You’ll learn how to use time series decomposition plots to visualize each of these components. Then you’ll get hands on practice building out an ETS model in Alteryx.
• you’ll learn how to build and use ARIMA models. ARIMA stands for autoregressive, integrated, moving average, which are the inputs for ARIMA models. You’ll learn how to stationarize data through differencing, a process that prepares data for ARIMA modeling. You’ll learn the different techniques used in seasonal vs. non-seasonal data. Then you’ll get hands on practice building out an ARIMA model in Alteryx.
• You’ll learn how to use holdout samples to compare models and select the best one for a business problem. You’ll also learn how to visualize your forecasts through various plots.