Data Science: R Basics Bootcamp

This facilitated Bootcamp enables you to complete the standard Data Science: R Basics course in less time! A foundation in R will ensure you know how to wrangle, analyze and visualize data.
• Live Instructor Q&A Sessions
• Learner Success Coach support
• Peer Learning Community
• Career guidance with an experienced Data Scientist

1 Week 8 - 16 Hours recommended
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Please select the start dates for your courses below.

Scheduled Start:

What is a Bootcamp?

Our facilitated bootcamps focus on rapid skill acquisition by progressing you through a standard course on an accelerated schedule with peers who are committed to progressing on pace. Our bootcamps include:

  • Live kick-off event
  • Instructor facilitated Q&A for expert feedback and coaching
  • Learner Success Support: welcome call, advising sessions, personalized pace reminders
  • 24/7 help desk

About this course

This bootcamp will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states.

We’ll cover R’s functions and data types, then tackle how to operate on vectors and when to use advanced functions like sorting. You’ll learn how to apply general programming features like “if-else,” and “for loop” commands, and how to wrangle, analyze and visualize data.

We help you develop a skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

This course can be used towards completion of a Professional Certificate in Data Science .

What you will learn

  • Basic R syntax
  • Foundational R programming concepts such as data types, vectors arithmetic, and indexing
  • How to perform operations in R including sorting, data wrangling using dplyr, and making plots

Meet your instructors

Rafael Irizarry

Rafael Irizarry

Professor of Biostatistics at Harvard University
Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data. During this time, he has also has taught several classes, all related to applied statistics. Dr. Irizarry is one of the founders of the Bioconductor Project, an open source and open development software project for the analysis of genomic data. His publications related to these topics have been highly cited and his software implementations widely downloaded.

Leonardo Palomera

Leonardo Palomera, through his professional and academic experiences, has become a specialist in data analytics for a variety of subjects including education, statistics, economics, and finance. Currently Leonardo works as a Data Scientist with Pearson Advance to support our goal of personalizing support that leads to high course completion rates. Additionally, Leonardo has held teaching positions at University of Southern California (USC), University of California, Los Angeles (UCLA), University of Colorado, Boulder, University of Denver, and California State University, Long Beach (CSULB). His goal is to empower students to gain the knowledge and skills they need to conduct robust analytics on a host of real-world problems.

Frequently asked questions

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Research statement
By registering as an online learner in our open online courses, you are also participating in research intended to enhance HarvardX’s instructional offerings as well as the quality of learning and related sciences worldwide. In the interest of research, you may be exposed to some variations in the course materials. HarvardX does not use learner data for any purpose beyond the University’s stated missions of education and research. For purposes of research, we may share information we collect from online learning activities, including Personally Identifiable Information, with researchers beyond Harvard. However, your Personally Identifiable Information will only be shared as permitted by applicable law, will be limited to what is necessary to perform the research, and will be subject to an agreement to protect the data. We may also share with the public or third parties aggregated information that does not personally identify you. Similarly, any research findings will be reported at the aggregate level and will not expose your personal identity.

Please read the edX Privacy Policy for more information regarding the processing, transmission, and use of data collected through the edX platform.

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Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

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Pacing

Instructor-paced