Introduces statistical genomics with an emphasis on next generation sequencing and microarrays. Covers the key capabilities of the Bioconductor project (a widely used open source software project for the analysis of high-throughput experiments in genomics and molecular biology and rooted in the open source statistical computing environment R). Also introduces statistical concepts and tools necessary to interpret and critically evaluate the bioinformatics and computational biology literature. Includes an overview of preprocessing and normalization, batch effects, statistical inference, multiple comparisons. Intended for students with a background in statistics or biology, but not necessarily both. Assumes some familarity with the R statistical language (a student without any experience in this language can still take the class but will need to set aside additional time to learn R).