Discover big data: work with airline data to learn the fundamentals of the R platform.
Weekly study4 hours
Introduction to R for Data Science
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Work with airline data to learn the fundamentals of the R platform.
We live in a data driven world. So how can we make the most of it? Have you ever wondered how data-driven decisions are made?
This course will use airline data to demonstrate key concepts involved in the analysis of big data. In this course you will learn how to use the R platform to manage data. The course serves as an introduction to the R software. It lays the foundation for anyone to begin studying data science and its applications, or to prepare learners to take more advanced courses related to data science, such as machine learning and computational statistics.
What topics will you cover?
- Download, install, and use the R platform
- Import data into R and visualize data
- Use vectors and vectorized functions, including some of the tapply functions
- Manipulate data into desired formats, including cleaning and verifying data
- Predict business performance
- Make data-driven decisions about your industry
Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Perform an import of data into R
- Utilize vectors and vectorized functions, including some of the apply functions
- Utilize basic data structures such as data frames, strings, dates, lists, etc.
Who is the course for?
This course is for anyone who is interested in discovering more about data. Beginners in using R are welcome. Prior experience is not required.
What software or tools do you need?
You will need to download, install, and use the R platform. A desktop or laptop computer is also needed to take this course as opposed to a mobile device.
What do people say about this course?
Who will you learn with?
Mark is an Associate Professor, and Undergraduate Chair at Department of Statistics, Purdue University, and Associate Director for the NSF Center for Science of Information.
I am a graduate student in the Department of Statistics at Purdue University. Currently, I am helping coordinate the course: Introduction to R for Data Science.
Learning on FutureLearn
Your learning, your rules
- Courses are split into weeks, activities, and steps to help you keep track of your learning
- Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
- Stay motivated by using the Progress page to keep track of your step completion and assessment scores
Join a global classroom
- Experience the power of social learning, and get inspired by an international network of learners
- Share ideas with your peers and course educators on every step of the course
- Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others
Map your progress
- As you work through the course, use notifications and the Progress page to guide your learning
- Whenever you’re ready, mark each step as complete, you’re in control
- Complete 90% of course steps and all of the assessments to earn your certificate
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