Data Analysis for Life Sciences

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Educational Hours
Advanced
Language :
English
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About this Course

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.

Instructors

Rafael Irizarry
Rafael Irizarry
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.
Michael Love
Michael Love
Michael Love is Assistant Professor in the Departments of Biostatistics and Genetics at UNC Gillings School of Global Public Health. Dr. Love received his bachelor’s in mathematics in 2005 from Stanford University, his master’s in statistics in 2010 from Stanford University, and his Ph.D. in Computational Biology in 2013 from the Freie Universität Berlin. Dr. Love uses statistical models to infer biologically meaningful patterns from high-throughput sequencing data, and develops open-source statistical software for the Bioconductor Project.