Rafael Irizarry
Professor of Biostatistics, T.H. Chan School of Public Health

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.

Faculty Courses

Online

Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.

Price
Free*
Registration Deadline
Available now
Online

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008.

Price
Free*
Registration Deadline
Available now
Online

Show what you’ve learned from the Professional Certificate Program in Data Science.

Price
Free*
Registration Deadline
Available now
Online

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.

Price
Free*
Duration
5 weeks long
Registration Deadline
Available now
Online

The structure, annotation, normalization, and interpretation of genome scale assays.

Price
Free*
Duration
4 weeks long
Registration Deadline
Available now
Online

Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data.

Price
Free*
Duration
5 weeks long
Registration Deadline
Available now
Online

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

Price
Free*
Duration
4 weeks long
Registration Deadline
Available now
Online

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

Price
Free*
Duration
4 weeks long
Registration Deadline
Available now