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Udacity

Time Series Forecasting

via Udacity

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Overview

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.

Syllabus

  • 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.

Taught by

Tony Moses

Reviews

3.0 rating, based on 1 Class Central review

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    Henry Tan
    Include a more comprehensive content will be encouraged. With a supportive fundamental knowledge available together, it will be easier to move forward to an advanced stage.
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