Sensor Fusion and Multi-Object Tracking edX - online learning platform

Overview

This Sensor Fusion and Multi-Object Tracking program in collaboration with Chalmers University of Technology - ChalmersX is derived from master level courses. It starts by introducing the basics of Bayesian statistics and recursive estimation theory and then gradually introduces more advanced concepts. The program offers a unique opportunity to gain practical knowledge in sensor fusion and multi-object tracking algorithms (filters).

Key Facts

Give your career a boost by mastering how to fuse information from a variety of different sensors, such as, radar, lidar and camera, for accurate object positioning and tracking of moving objects.The target audience for this program are engineers in the automotive industry who need to tackle problems related to perceiving the traffic situation around an autonomous vehicle. This course is also aimed at students with a bachelor's degree who want to pursue master level studies in automotive engineering.

By the end of this program, you will be able to contribute to the development of sensor fusion and tracking applications for self-driving vehicles. Most of the involved methods, however, are more general and can be used for surveillance or to track, e.g., biological cells, sports athletes or space debris.

Job Outlook

• With the rapid growth of the self-driving vehicles market, there is a high demand for engineers with expertise in designing electric vehicles.
• This demand is expected to continue to grow in the coming years, with many countries setting ambitious targets for the adoption of electric vehicles and the development of supporting infrastructure.