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.

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.

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

Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.

Apply tools of single-variable calculus to create and analyze mathematical models used by real practitioners in social, life, and...

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

This course focuses on studying methods that allow a machine to learn and analyze images and video using geometry and statistical...

Supervise learning algorithms, such as regression analysis, support-vector machines, and neural networks have demonstrated...

Learn various topics within linear algebra.

This course is an introduction to statistical methods used in biological and medical research