Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “...

Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train...

Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own...

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

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.

Combine literary research with data science to find answers in unexpected ways. Learn basic coding tools to help save time and...

Join Harvard University instructor Pavlos Protopapas in this online course to learn how to use Python to harness and analyze data.

Learn introductory programming and data analysis in MATLAB, with applications to biology and medicine.

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