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Course
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Applied Time Series Analysis and Forecasting with R
R and time series analysis go together hand-in-hand. In this course, you'll learn how to effectively use R and the forecast package to practice time series analysis and work on real-world projects and data.
What you'll learn
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
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: r-tutorials.com
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