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

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

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

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

A focus on the techniques commonly used to perform statistical inference on high throughput data.

Learn to use R programming to apply linear models to analyze data in life sciences.

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Develop skills in digital research and visualization techniques across subjects and fields within the humanities.

Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal...

Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results,...

In this course, we look at how ongoing workplace changes related to practice, technology and data have been accelerated by the...

Dive into advanced methods for data wrangling, data visualization, and statistical modeling and prediction.

In your setting, you will learn a step-by-step process for engaging in collaborative inquiry and using a range of data sources to...