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Master key concepts using the R programming language

XSeries Program in
Data Analysis for Life Sciences
HarvardX

What you will learn

  • Basic statistical concepts and R programming skills necessary for analyzing data in the life sciences
  • The underlying mathematical basics of linear models useful for data analysis in the life sciences
  • The techniques commonly used to perform statistical inference on high throughput data
  • Several techniques that are widely used in the analysis of high-dimensional data

Currently, biomedical research groups around the world are producing more data than they can handle.

The training and skills acquired by taking the Data Analysis for Life Sciences XSeries will result in greater success in biological discovery and improving individual and population health.

In this XSeries, you will gain the tools to analyze and interpret life sciences data. You will learn the basic statistical concepts and R programming skills necessary for analyzing real data.

R is an open source free statistical software and is the most widely used data analysis platforms among academic statisticians.

Taught by Rafael Irizarry from the Harvard T.H. Chan School of Public Health, who for the past 15 years has focused on the analysis of genomics data, this XSeries is perfect for anyone in the life sciences who wants to learn how to analyze data. Problem sets will require coding in the R language to ensure learners fully grasp and master key concepts.

Expert instruction
4 graduate-level courses
4-6 months
0 hours of effort
$221.40
$246USD
For the full program experience

Courses in this program

  1. HarvardX's Data Analysis for Life Sciences XSeries

  2. Not currently available

    An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

  3. Not currently available

    Learn to use R programming to apply linear models to analyze data in life sciences.

  4. Not currently available

    A focus on the techniques commonly used to perform statistical inference on high throughput data.

  5. Not currently available

    A focus on several techniques that are widely used in the analysis of high-dimensional data.

  6. This program was supported in part by NIH grant R25GM114818.

    HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

    HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

    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 [email protected] and/or report your experience through the edX contact form.

Meet your instructors

from Harvard University (HarvardX)
Rafael Irizarry
Professor of Biostatistics
Harvard University
Michael Love
Assistant Professor, Departments of Biostatistics and Genetics
UNC Gillings School of Global Public Health

Experts from HarvardX committed to teaching online learning

Enrolling Now

$221.40
$246USD
4 courses in 4-6 months
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