Statistics Courses

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

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

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.

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

Build practical skills that will prepare you to interpret data, test ideas, and apply predictive and AI insights to real-world business decisions in this course from Harvard Business School (HBS) Online.

Learn inference and modeling: two of the most widely used statistical tools in data analysis.

Increase your quantitative reasoning skills through a deeper understanding of probability and statistics, with the engaging “Fat Chance” approach that’s made this course a favorite among learners worldwide.

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

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

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

This 17-week online credential program from Harvard Business School (HBS) Online will teach you the fundamental skills professionals need to succeed today.  

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008.