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Udacity

Time Series Forecasting

via Udacity

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

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Reviews

3.0 rating, based on 1 reviews

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  • Henry Tan completed this course, spending 5 hours a week on it and found the course difficulty to be medium.

    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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