Hands-on labs included
After-course coaching available
After-course computing sandbox
#1269
Time Series Analysis Using R
Course 1269
- Duration: 1 day
- Language: English
- Level: Foundation
A time series is simply a series of data points arranged chronologically.
Time series appear in many contexts.
- Finance (e.g. stock prices)
- Marketing (e.g. new customers, sales)
- Health (e.g. infections, deaths)
- Science (e.g earthquakes)
- ...and many, many more
Time Series Analysis Delivery Method
In-Person
Online
Time Series Analysis Course Information
In this course, you will:
- Work with the R statistical modeling language to analyze data.
- Import internal and external data sources into R.
- Work with time-series data.
- Visualize time-series data.
- Perform automated forecasting using Prophet.
- Consider the potential impact of machine learning on time series analysis.
- Leverage continued support with after-course one-on-one instructor coaching and computing sandbox.
Prerequisites
None.
Time Series Analysis Instructor-Led Course Outline
- Basics of writing R scripts
- Viewing data sets in R
- Querying and Saving Data in R
- Exploratory Data Analysis
- Visualizing Data
- Transforming Data
- Time Series in R
- Creating Time Series
- Querying and Data Manipulation
- Combining Time Series
- Rate of Change
- Applying Functions to Intervals
- Plotting Basics
- Univariate Time Series
- Multivariate Time Series
- Generate Forecasts using Prophet
- Forecast COVID-19 Cases
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Time Series Analysis FAQs
No. You will be taught basic R skills as part of the course.
This is an introductory course. If you have a favorite time series technique, then you are possibly already beyond this course. The focus is very much on the basics. We make extensive use of the popular `xts` package and introduce Meta's (Facebook's) Prophet library.
The focus of the course is on time series analysis. R is merely used as a tool to that end. So, yes---the concepts will translate to your preferred environment.
Yes. There are various opportunities to apply the ideas presented to real-world time series data.