
Online or onsite, instructor-led live Reinforcement Learning training courses demonstrate through interactive hands-on practice how to create and deploy a Reinforcement Learning system.
Reinforcement Learning training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. The UK onsite live Reinforcement Learning trainings can be carried out locally on customer premises or in NobleProg corporate training centres.
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Testimonials
I liked how engaging Gunnar was and going through the exercises. I really enjoyed it
Premier Partnership
Course: Fundamentals of Reinforcement Learning
Abhi always made sure we were following along. Good mix of practice and theory.
Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Course: Deep Reinforcement Learning with Python
The informal exchanges we had during the lectures really helped me deepen my understanding of the subject
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Course: Deep Reinforcement Learning with Python
Reinforcement Learning Course Outlines
- Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning.
- Apply advanced Reinforcement Learning algorithms to solve real-world problems.
- Build a Deep Learning Agent.
- Install and apply the libraries and programming language needed to implement Reinforcement Learning.
- Create a software agent that is capable of learning through feedback instead of through supervised learning.
- Program an agent to solve problems where decision making is sequential and finite.
- Apply knowledge to design software that can learn in a way similar to how humans learn.
- Understand the relationships and differences between Reinforcement Learning and machine learning, deep learning, supervised and unsupervised learning.
- Analyze a real-world problem and redefine it as Reinforcement Learning problem.
- Implementing a solution to a real-world problem using Reinforcement Learning.
- Understand the different algorithms available in Reinforcement Learning and select the most suitable one for the problem at hand.
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