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.
Overview
Syllabus
- Manipulating Time Series Data in R
- Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
- Time Series Analysis in R
- Learn the core techniques necessary to extract meaningful insights from time series data.
- ARIMA Models in R
- Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
- Forecasting in R
- Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.
- Visualizing Time Series Data in R
- Learn how to visualize time series in R, then practice with a stock-picking case study.
- Case Study: Analyzing City Time Series Data in R
- Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.
Taught by
David S. Matteson, David Stoffer, Lore Dirick, Matt Isaacs, Arnaud Amsellem, Rob J. Hyndman, and Harrison Brown
