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Reinforcement Learning

Master Reinforcement Learning concepts, algorithms, and applications through interactive coding exercises and real-world problem-solving techniques online
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Overview

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Learning outcomes

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Course content

1

Markov Decision Processes

2

Policy Gradient Methods

3

Q-Learning Algorithms

4

Deep Reinforcement Learning

5

Exploration Strategies

Career Path

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Key facts

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Why this course

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People also ask

Everything you need to know before you start

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We offer immediate access to our course materials through our open enrollment system. This means:

  • The course starts as soon as you pay the course fee, instantly
  • No waiting periods or fixed start dates
  • Instant access to all course materials upon payment
  • Flexibility to begin at your convenience

This self-paced approach allows you to begin your professional development journey immediately, fitting your learning around your existing commitments.

We offer two flexible learning paths to suit your schedule:

  • Fast Track: Complete in 1 month with 3-4 hours of study per week
  • Standard Mode: Complete in 2 months with 2-3 hours of study per week

You can progress at your own pace and access the materials 24/7.

There are no formal entry requirements for this course. You just need:

  • A good command of English language
  • Access to a computer/laptop with internet
  • Basic computer skills
  • Dedication to complete the course
Ready when you are
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Assessment is done through:

  • Multiple-choice questions at the end of each unit
  • You need to score at least 60% to pass each unit
  • You can retake quizzes if needed
  • All assessments are online

Upon successful completion, you will receive:

  • A digital certificate from London School of Planning and Management
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee
Open enrolment · Start today

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Why people choose us for their career

Trusted by professionals worldwide

Verified outcomes from learners who finished the course and put it to work.

4.5
Based on 4 learner reviews · 4 countries
98%
Would recommend
100%
Verified learners
2026
Cohort active
Completed from United Kingdom
JM
James Mitchell
GB · Course completed

I recently completed the Reinforcement Learning course at Stanmore School of Business, and I must say it was an absolute game-changer. The course content was incredibly comprehensive, covering everything from the basics of RL to advanced topics like deep reinforcement learning. The quality of the course materials was top-notch, with excellent video lectures, quizzes, and assignments that really helped me grasp the concepts. I was able to apply the knowledge I gained to my own project, which involved training an agent to play a game using Q-learning. The results were amazing, and I was able to achieve a significant improvement in the agent's performance. Overall, I'm extremely satisfied with the course and would highly recommend it to anyone looking to learn about reinforcement learning.

LH
Luis Hernandez
MX · Course completed

I took the Reinforcement Learning course at Stanmore School of Business and it was a really great experience. The course covered a lot of practical topics, like how to implement RL algorithms in Python and how to use popular libraries like Gym and PyTorch. I liked that the course had a lot of hands-on exercises and projects, which helped me learn by doing. One thing that I found really useful was the section on exploration-exploitation trade-offs, which I wasn't familiar with before. The instructor did a great job of explaining it in a way that was easy to understand. My only suggestion would be to add more advanced topics, like multi-agent RL or RL for robotics. Overall, I'd definitely recommend this course to anyone looking to get started with RL.

RA
Raj Anand
SG · Course completed

Wow, just wow! The Reinforcement Learning course at Stanmore School of Business was absolutely fantastic! I was a bit skeptical at first, but the course completely exceeded my expectations. The instructor was so enthusiastic and passionate about the subject, it was infectious! I loved how the course covered not just the theory, but also the practical applications of RL. We got to work on some really cool projects, like training an agent to navigate a maze and another to play a game of Pong. The feedback from the instructor was always prompt and helpful, and the community of students was really supportive. I gained so much confidence in my ability to work with RL algorithms and I'm already applying what I learned to my own research project. If you're interested in RL, you have to take this course - it's a no-brainer!

HR
Hassan Rahman
AE · Course completed

I found the Reinforcement Learning course at Stanmore School of Business to be quite detailed and thorough. The course materials were well-organized and easy to follow, and the instructor did a good job of explaining the concepts. I particularly appreciated the section on policy gradients, which I found to be really interesting. The course also covered some advanced topics, like actor-critic methods and deep deterministic policy gradients. One thing I liked was that the course included some case studies of real-world applications of RL, which helped to illustrate the concepts and make them more concrete. My only suggestion would be to provide more feedback on the assignments, as I sometimes found it difficult to gauge my own understanding of the material. Overall, I'd recommend this course to anyone looking for a comprehensive introduction to RL.





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Recently updated!

May 2026