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Time Series in R

Updated 03/2026
Learn how to extract meaningful insights from time series data in R. Explore how to model, forecast, and visualize time series data.
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RProbability & Statistics25 hr3,597

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Track Description

Time Series in R

Learn how to extract meaningful insights from time series data in R with this six-course track. Explore how to model, forecast, and visualize time series data using R programming. Time series are all around us, from server logs to high-frequency financial data. With this track, you’ll learn how to manipulate time series data, how to use R for time series analysis, and how time series modeling works. You’ll also cover time series forecasting in R, learning how to make predictions about the future based on data. After you finish learning how to visualize time series data, you’ll complete a case study using real data and the R skills you’ve developed so far. By the time you complete this track, you’ll have the confidence to work with your own time series data in R.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Manipulating Time Series Data in R

    Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

  • Course

    3

    ARIMA Models in R

    Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

  • Course

    4

    Forecasting in R

    Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Time Series in R
6 Courses
Track
Complete

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FAQs

Is this Track suitable for beginners?

This track is suitable for beginners. No prior knowledge is necessary, but if you have some basic familiarity with R programming, it will deepen your understanding of time series analysis.

What is the programming language of this Track?

This Track requires knowledge of R programming.

Which jobs will benefit from this Track?

Jobs in financial markets, activities that involve critical infrastructure or utilities, and transport and logistics can all benefit from this Track.

How will this Track prepare me for my career?

This Track will equip you with the skills to analyze, interpret, and forecast time series data. You will develop a strong understanding of R programming as well as knowledge of important libraries, concepts, and methods.

How long does it take to complete this Track?

This Track normally takes approximately 25 hours to complete.

What's the difference between a skill track and a career track?

A skill track focuses on teaching domain-specific technical skills and the necessary knowledge to build a successful career, whereas a career track focuses on developing deeper expertise for a given profession.

What datasets will be used?

The datasets used in this Track are generally created from real-world examples.

Are specific libraries required?

To get the most out of this Track, you'll need knowledge of important R libraries, such as xts and zoo.

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