We recently received funding from the NIH BD2K initiative to develop MOOCs for biomedical data science. Our first offering will be version 2 of my Data Analysis for Genomics course which will launch on January 19. In this version, the course will be turned into an 8 course series and you can get a certificate in each one of them. The motivation for doing this is to go more in-depth into the different topics and to provide different entry points for students with different levels of expertise. We provide four courses on concepts and skills and four case-study based course. We basically broke the original class into the following eight parts:
- Statistics and R for the Life Sciences
- Introduction to Linear Models and Matrix Algebra
- Advanced Statistics for the Life Sciences
- Introduction to Bioconductor
- Case study: RNA-seq data analysis
- Case study: Variant Discovery and Genotyping
- Case study: ChIP-seq data analysis
- Case study: DNA methylation data analysis
You can follow the links to enroll. While not required, some familiarity with R and Rstudio will serve you well so consider taking Roger’s R course and Jeff’s Toolbox course before delving into this class.
In years 2 and 3 we plan to introduce several other courses covering topics such as python for data analysis, probability, software engineering, and data visualization which will be taught by a collaboration between the departments of Biostatistics, Statistics and Computer Science at Harvard.
Announcements will be made here and on twitter: @rafalab