How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping.
Computing for Data Analysis
The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data. The goal of this course, part of the Analytics: Essential Tools and Methods MicroMasters program,…
