
Reinforcement Learning for Optimisation and Control
Explore Reinforcement Learning for Optimisation and Control with a focus on rewards and reinforcement learning environments, including an introductory example, dedicated imagery, practice and a knowledge check.
Turn Knowledge into Capability
A reinforcement-learning agent learns behaviour against a defined reward. Poor reward design can create unwanted behaviour; simulator performance without environment-gap and constraint checks is not approval for real-process control.
This edition contains an introductory learning sample. Full specialist material will be added later. The listed time applies only to this sample.
The material is for introductory learning and practice. It does not confer an operational or professional qualification.
What You Will Learn
Who Is This Programme for?
Data, AI and Digital Transformation Professionals
Prerequisites
Basic familiarity with the subject vocabulary and technical reports. No specialist equipment is needed for this introductory sample.
Your Practice Task
Define a reward objective, possible unintended behaviour and evaluation constraint for a fictional training environment.
Your learning space includes reading, an image, flashcards, a table, slides and feedback-based practice. Activity progress is saved, and a short assessment follows the completed lessons.
Further Reading
Before You Start
What Does the Sample Include?
This edition contains two short lessons, interactive activities and a sample assessment. The listed duration applies to this edition; the full specialist programme will follow.
How Do I Access the Learning Material?
Sign in and select “Enrol in This Programme”. The course appears in your learning space, where you can start or resume its activities.
What Kind of Certificate Does This Edition Offer?
Complete the required activities and pass the assessment to access a platform demonstration certificate. It is not an official equipment-vendor or professional certification.
Learner Comments
Moderated comments on this programme’s videos
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