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Reinforcement Learning

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Overview

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Learning outcomes

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Course content

1

Introduction To Reinforcement Learning

2

Markov Decision Processes

3

Deep Reinforcement Learning

4

Policy Gradient Methods

5

Value-Based Methods

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
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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 Business and Administration
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee
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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 States
MC
Michael Carter
US · Course completed

I just finished the Reinforcement Learning course at Stanmore School of Business and I'm blown away! The course content was incredibly comprehensive and helped me achieve my learning goals of understanding the fundamentals of RL. I was able to apply the concepts to a project at work, where I implemented a Q-learning algorithm to optimize a recommendation system. The quality of the course materials was top-notch, with engaging video lectures and relevant assignments. Overall, I'm extremely satisfied with my learning experience and I highly recommend this course to anyone interested in RL.

LH
Leila Hassan
EG · Course completed

I found the Reinforcement Learning course to be quite informative and practical. The instructor did a great job of explaining complex concepts in a simple way, making it easy to follow along. I particularly enjoyed the section on policy gradients, which I was able to apply to a personal project involving a robotic arm. The course materials were well-organized and the assignments were challenging but manageable. My only suggestion would be to include more real-world examples from the Middle East region. Overall, I'm happy with my learning experience and I would recommend this course to others.

KN
Kaito Nakamura
JP · Course completed

Wow, just wow! The Reinforcement Learning course at Stanmore School of Business was an absolute game-changer for me! I was able to learn about the latest advancements in RL, including deep RL and imitation learning. The course materials were incredibly detailed and the instructor was very responsive to questions. I was able to apply the concepts to a research project, where I developed a novel RL algorithm for autonomous driving. I'm so grateful for the opportunity to take this course and I would highly recommend it to anyone interested in AI and machine learning.

RS
Rafaela Silva
BR · Course completed

I took the Reinforcement Learning course at Stanmore School of Business and it was a great experience! The course content was really comprehensive and covered all the key topics in RL. I liked how the instructor used a lot of examples and case studies to illustrate the concepts, making it easier to understand. I was able to apply the concepts to a project at work, where I developed a RL-based system for optimizing energy consumption. The course materials were good, but I think it would be helpful to include more feedback from peers and instructors. Overall, I'm happy with my learning experience and I would recommend this course to others.





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Recently updated!

May 2026