Course info
Jan 24, 2019
2h 3m

The R language and software environment are key when producing and analyzing time series data. In this course, Applied Time Series Analysis and Forecasting with R, you’ll learn how to apply modern day time series models on real-world data. First, you'll discover how to design time series models containing trend or seasonality. Next, you'll delve further into models, such as ARIMA, exponential smoothing, and neural networks. Finally, you'll learn how to visualize time series interactively with dygraphs. When you're finished with this course, you'll have the necessary knowledge to apply standard time series models on a univariate time series.

About the author
About the author

Martin is a trained biostatistician, programmer, consultant and data science enthusiast. His main objective: Explaining data science in a straightforward way. You can find his latest work over at:

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
(Music) Welcome to Applied Time Series Analysis and Forecasting with R. This is Martin Burger for Pluralsight. R and time series analysis go together perfectly. There are a lot of R packages available for this topic. Therefore, R is a very good idea to select for this type of data analysis. This course shows you how to apply R on real world time series data. In fact, this is a very hands-on practical course featuring three time series analysis projects. These three projects will show you how to practically work with either trend or seasonality and the combination of both. By the end of this course, you will know how to use R to implement and visualize standard time series models like ARIMA, exponential smoothing, or even neural networks. Now to fully benefit from this course, you should have some basic R skills, and of course it is a good idea to have R and RStudio ready on your machine with all the required add-on packages we discussed in the course. You can actually see this course as the applied side of my other course on Beginning Time Series Analysis and Forecasting with R. So these two courses complement each other quite a bit. I really hope you will use this course to your advantage and practice time series analysis in R.