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Forecasting in R

Intermediate
4.9+
15 reviews
Updated 04/2025
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.
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RProbability & Statistics5 hours18 videos55 Exercises4,450 XP50,094Statement of Accomplishment

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Course Description

Use Forecasting in R for Data-Driven Decision Making

This course provides an introduction to time series forecasting using R.

Forecasting involves making predictions about the future. It is required in many situations, such as deciding whether to build another power generation plant in the next ten years or scheduling staff in a call center next week.

Forecasts may be needed several years in advance (for the case of capital investments), or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, reliable forecasting is essential to good data-driven decision-making.

Build Accurate Forecast Models with ARIMA and Exponential Smoothing

You’ll start this course by creating time series objects in R to plot your data and discover trends, seasonality, and repeated cycles. You’ll be introduced to the concept of white noise and look at how you can conduct a Ljung-Box test to confirm randomness before moving on to the next chapter, which details benchmarking methods and forecast accuracy.

Being able to test and measure your forecast accuracy is essential for developing usable models. This course reviews a variety of methods before diving into exponential smoothing and ARIMA models, which are two of the most widely-used approaches to time series forecasting.

Before you complete the course, you’ll learn how to use advanced ARIMA models to include additional information in them, such as holidays and competitor activity.

Prerequisites

Time Series Analysis in R
1

Exploring and visualizing time series in R

Start Chapter
2

Benchmark methods and forecast accuracy

Start Chapter
3

Exponential smoothing

Start Chapter
4

Forecasting with ARIMA models

Start Chapter
5

Advanced methods

Start Chapter
Forecasting in R
Course
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*4.9
from 15 reviews
93%
7%
0%
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0%
  • Dymph W.
    3 months

    I really enjoyed this course. The subjects are clearly explained and the buildup is easy to follow. The only thing I would improve is more practise in the interpretation of the graphs in relation to the different ETS and ARIMA models

  • Christian U.
    11 months

    Great Course on Forecasting with R!

  • Yasuhisa Y.
    about 1 year

    very good

  • Mi s.
    over 1 year

    A very, very good course. The instructor is not only extremely competent in his field, but also a master at teaching complex issues in a clear way.

  • Isobel M.
    over 1 year

    I've recently got hooked on Professor Hyndman's work, specifically time series forecasting in R. This course is a perfect complement to the latest version of his book (available free online with videos) and fills in some gaps for those that learn by playing/doing and hearing explanations rather than reading them.

"I really enjoyed this course. The subjects are clearly explained and the buildup is easy to follow. The only thing I would improve is more practise in the interpretation of the graphs in relation to the different ETS and ARIMA models"

Dymph W.

"Great Course on Forecasting with R!"

Christian U.

"very good"

Yasuhisa Y.

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