Courses

Learn about the development of 2D and 3D interactive games in this hands-on course, as you explore the design of games such as Super Mario Bros., Pokémon, Angry Birds, and more.

An introduction to the intellectual enterprises of computer science and the art of programming.

A gentle introduction to programming that prepares you for subsequent courses in coding.

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

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

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

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

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

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, reproduce them yourself, and communicate them to others.

Show what you’ve learned from the Professional Certificate Program in Data Science.

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

Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. Before you know it, you’ll be implementing an entire TinyML application.