Time Series Forecasting

The Time Series Forecasting course provides students with the foundational knowledge to build and apply time series forecasting models in a variety of business contexts. You will learn:

• The key components of time series data and forecasting models
• How to use ETS (Error, Trend, Seasonality) models to make forecasts
• How to use ARIMA (Autoregressive, Integrated, Moving Average) models to make forecasts

Throughout this course you’ll also learn the techniques to apply your knowledge in a data analytics program called Alteryx.

This course is part of the Business Analyst Nanodegree Program.

• Time Series Fundamentals
• Learn what attributes make data a time series.,Get introduced to a variety of simple forecasting methods.,Learn about seasonality, trends, and cyclical patterns.
• ETS Models
• Learn how to build and use ETS models.,Use decomposition plots to visualize time series data.,Get practice building an ETS model in Alteryx.
• ARIMA Models
• Learn how to build and use ARIMA models.,Learn the techniques used in seasonal and non-seasonal ARIMAs.,Get practice building an ARIMA model in Alteryx.
• Analyzing and Visualizing Results
• Learn how to interpret time series model results.,Learn how to use holdout samples to compare forecasting models.,Visualize your forecasts through various plots.