Build a foundation in R and learn how to wrangle, analyze, and visualize data.

Build a foundation in R and learn how to wrangle, analyze, and visualize data.

Learn basic data visualization principles and how to apply them using ggplot2.

Learn to process and convert raw data into formats needed for analysis.

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

Learn the concepts and techniques that make up the foundation of data science and machine learning.

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

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

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

This course introduces learners to Machine Learning Operations (MLOps) through the lens of TinyML (Tiny Machine Learning). Learners explore best practices to deploy, monitor, and maintain (tiny) Machine Learning models in production at scale.

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

Become a UX data scientist! From qualitative data analysis to big data Web analytics, you will be able to leverage insights from data to make empirically-based recommendations.