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شهادة في تعلم التعزيز (Foundation)

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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

Value Functions And Bellman Equations

4

Policy Evaluation And Improvement

5

Dynamic Programming Methods

6

Monte Carlo Methods

7

Temporal‑Difference Learning

8

Deep Reinforcement Learning Foundations

9

Exploration Strategies And Exploitation

10

Ethics And Applications Of Reinforcement Learning

Career Path

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Key facts

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Why this course

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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 Planning and Management
  • 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 Kingdom
ST
Sarah Thompson
GB · Course completed

I found the course both engaging and practical. The sections on policy gradients and reward shaping helped me finish a personal project where I trained an agent to navigate a simulated city, which I later showcased at a local meetup. The video quality was top‑notch and the quizzes reinforced the key concepts nicely. It was a relaxed, yet thorough learning journey that matched my goals perfectly.

MC
Michael Carter
US · Course completed

The Foundation in Reinforcement Learning course exceeded my expectations. The structured modules on Markov Decision Processes and Q‑learning gave me a solid theoretical base, while the hands‑on Python notebooks let me implement a trading bot that actually improved my portfolio's risk‑adjusted returns. The instructor’s explanations were clear and the supplemental reading list was spot‑on for deeper dives. Overall, the experience was professional and highly rewarding.

AP
Ananya Patel
IN · Course completed

What a fantastic introduction to reinforcement learning! The course broke down complex ideas like deep Q‑networks into bite‑size examples using TensorFlow, enabling me to build a game‑playing AI within a week. The downloadable slide decks and code snippets were incredibly useful for my research, and the instructor’s enthusiastic tone kept me motivated throughout. I’m now confident to pursue advanced RL topics.

ZD
Zanele Dlamini
ZA · Course completed

The curriculum was detailed and relevant to real‑world problems. I especially appreciated the module on multi‑agent systems, which I applied to optimize routing for a small logistics startup in Johannesburg. The case studies and interactive simulations were well‑crafted, and the community forum provided quick answers to my questions. This course gave me practical skills I can immediately use in my job.

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Skills gained

Data Analysis
Problem Solving
Critical Thinking
Decision Making
These skills will be developed throughout the course


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Taught in English

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Recently updated!

May 2026