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ChalmersX: Decision-Making for Autonomous Systems

Learn effectivetactics for making keydecisionswhen working with autonomous, self-driving vehicles.

Decision-Making for Autonomous Systems
7 weeks
10–20 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

10,807 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Mar 19

About this course

Skip About this course

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 distinguished through its close collaboration with industry.

At a glance

  • Language: English
  • Video Transcript: English
  • Associated skills:Decision Making, Automotive Engineering, Reinforcement Learning, Mathematical Modeling, Autonomous System, Automotive Industry, Autonomous Vehicles

What you'll learn

Skip What you'll learn
  • Use Markov decision process (MDP) a mathematical framework for modellingdecision-making
  • Understand and apply reinforcement learning and event-based methods
  • Model and solve decision-making problems for autonomous systems

Who can take this course?

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