Data Analysis for Life Sciences

Master key concepts using the R programming language

This HarvardX professional certificate program gives learners the necessary skills and knowledge to analyze data in the life sciences.

Featuring faculty from:
4 months
2-4 hours per week
Certificate Price
$788.40 $876
Start the Data Science for Life Sciences Professional Certificate Series Today

What You'll Learn

Technological advances have transformed fields that rely on data by providing a wealth of information ready to be analyzed. From working with single genes to comparing entire genomes, biomedical research groups around the world are producing more data than they can handle and the ability to interpret this information is a key skill for any practitioner. The skills necessary to work with these massive datasets are in high demand, and this series will help you learn those skills.

Using the open-source R programming language, you’ll gain a nuanced understanding of the tools required to work with complex life sciences and genomics data. You’ll learn the mathematical concepts — and the data analytics techniques — that you need to drive data-driven research. From a strong foundation in statistics to specialized R programming skills, this series will lead you through the data analytics landscape step-by-step.

Taught by Rafael Irizarry from the Harvard T.H. Chan School of Public Health, these courses will enable new discoveries and will help you improve individual and population health. If you’re working in the life sciences and want to learn how to analyze data, enroll now to take your research to the next level.

The course will be delivered via edX and connect learners around the world. 

Courses in this Program

2–4 hours per week, for 4 weeks
An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

2–4 hours per week, for 4 weeks
Learn to use R programming to apply linear models to analyze data in life sciences.

2–4 hours per week, for 4 weeks
A focus on the techniques commonly used to perform statistical inference on high throughput data.

2–4 hours per week, for 4 weeks
A focus on several techniques that are widely used in the analysis of high-dimensional data.

Your Instructor

Rafael Irizarry

Rafael Irizarry

Professor of Biostatistics at Harvard University
Read full bio.

Michael Love

Michael Love

Assistant Professor, Departments of Biostatistics and Genetics at UNC Gillings School of Global Public Health
Read full bio.

Job Outlook

  • R is listed as a required skill in 64% of data science job postings and was Glassdoor’s Best Job in America in 2016 and 2017. (source: Glassdoor)
  • Companies are leveraging the power of data analysis to drive innovation. Google data analysts use R to track trends in ad pricing and illuminate patterns in search data. Pfizer created customized packages for R so scientists can manipulate their own data.
  • 32% of full-time data scientists started learning machine learning or data science through a MOOC, while 27% were self-taught. (source: Kaggle, 2017)
  • Data Scientists are few in number and high in demand. (source: TechRepublic)

Ways to take this program

When you enroll in this program, you will register for a Verified Certificate for all 4 courses in the Professional Certificate Series. 

Alternatively, learners can Audit the individual course for free and have access to select course material, activities, tests, and forums. Please note that Auditing the courses does not offer course or program certificates for learners who earn a passing grade.