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Time Series Forecasting

Course

Learn the fundamentals of time series forecasting and develop proficiency in ETS and ARIMA models, two the most commonly used models in forecasting.

Learn the fundamentals of time series forecasting and develop proficiency in ETS and ARIMA models, two the most commonly used models in forecasting.

Last Updated March 7, 2022

Prerequisites:

No experience required

Course Lessons

Lesson 1

Fundamentals of Time Series Forecasting

In this lesson 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.

Lesson 2

ETS Models

In this lesson 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.

Lesson 3

ARIMA Models

In this lesson 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.

Lesson 4

Analyzing and Visualizing Results

This lesson will demonstrate how to interpret the various results from time series model. 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.

Taught By The Best

Photo of Tony Moses

Tony Moses

Instructor

Tony Moses is a Solutions Engineer at Alteryx, Inc. He works with customers to help develop plans to solve complex business problems around data preparation, geospatial analysis and predictive analytics.

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