Decision-Making for Autonomous Systems - Top Free Course

What Will You Learn?

In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the coordination among multiple vehicles.

This course will teach you the fundamental mathematical model for many of these real-world problems. Key topics include Markov decision process, reinforcement learning and event-based methods as well as the modelling and solving of decision-making for autonomous systems.

This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge in decision-making models for autonomous systems.

Enhance your decision-making skills in automotive engineering by learning from Chalmers, one of the top engineering schools that is distinguished by its close collaboration with industry.

About This Course

Provider: edx.org
Format: Online
Duration: 7 weeks to complete [Approx.]
Target Audience: Advanced
Learning Objectives: By the end of the course, you will learn effective tactics for making key decisions when working with autonomous, self-driving vehicles.
Course Prerequisites: NA
Assessment and Certification: Earn a Certificate upon completion
Instructor: Jonas Sjöberg
Key Topics: Learn about Automotive Engineering, Automotive Industry, Autonomous Systems, Autonomous Vehicles, Decision Making, Mathematical Modeling, Reinforcement Learning, etc. 
Topic Covered:
- Use Markov decision process (MDP), a mathematical framework for modelling decision-making
- Understand and apply reinforcement learning and event-based methods
- Model and solve decision-making problems for autonomous systems