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Course Features

Price

Original price was: د.إ2,454.31.Current price is: د.إ75.08.

Study Method

Online | Self-paced

Course Format

Reading Material - PDF, article

Duration

17 hours, 25 minutes

Qualification

No formal qualification

Certificate

At completion

Additional info

Coming soon

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Overview

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Career Path

Who is this course for?

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Who is this course for
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Requirements

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    • Welcome & Course Introduction 00:10:00
    • Where to Get the Course Code 00:10:00
    • Strategy for Success 00:10:00
    • Course Structure & Learning Outcomes 00:10:00
    • Introduction to the Multi-Armed Bandit Problem 00:10:00
    • Real-World Applications of Explore-Exploit Dilemma 00:10:00
    • Epsilon-Greedy Strategy Explained 00:10:00
    • Updating the Sample Mean 00:10:00
    • Building Your First Bandit Program 00:10:00
    • Comparing Different Epsilon Strategies 00:10:00
    • Optimistic Initial Values 00:10:00
    • Understanding UCB1 00:10:00
    • Bayesian Thompson Sampling 00:10:00
    • Strategy Comparison: Epsilon-Greedy vs. UCB vs. Thompson Sampling 00:10:00
    • Nonstationary Bandits & Online Learning 00:10:00
    • Summary & Real-World Insights 00:10:00
    • What is Reinforcement Learning? 00:10:00
    • Unusual Behaviours in RL 00:10:00
    • Key Terms & Definitions in RL 00:10:00
    • Naive Approach to Tic-Tac-Toe 00:10:00
    • Core Components of an RL System 00:10:00
    • Reward Assignment Strategies 00:10:00
    • Value Function Explained 00:10:00
    • Tic-Tac-Toe – Code Structure Outline 00:10:00
    • Code Walkthrough: Game State Representation 00:10:00
    • Recursive State Enumeration 00:10:00
    • Environment Code Structure 00:10:00
    • Designing the RL Agent 00:10:00
    • Tic-Tac-Toe – Main Loop and Demonstration 00:10:00
    • Full Tic-Tac-Toe Agent in Action 00:10:00
    • Exercise: Improve the Agent 00:10:00
    • Understanding Gridworld 00:10:00
    • The Markov Property 00:10:00
    • MDPs: Definitions & Concepts 00:10:00
    • Future Rewards & Discounting 00:10:00
    • Introduction to the Value Function 00:10:00
    • Deep Dive into Value Functions 00:10:00
    • Bellman Equations in Practice 00:10:00
    • Optimal Policy & Value Function 00:10:00
    • Summary: Solving MDPs 00:10:00
    • Policy Evaluation with Dynamic Programming 00:10:00
    • Gridworld in Python 00:10:00
    • Structuring Your DP-Based RL Program 00:10:00
    • Coding Iterative Policy Evaluation 00:10:00
    • Policy Improvement Techniques 00:10:00
    • Policy Iteration in Python 00:10:00
    • Implementing Policy Iteration in Python 00:10:00
    • Windy Gridworld Policy Iteration 00:10:00
    • Value Iteration Overview 00:10:00
    • Value Iteration Implementation 00:10:00
    • Summary: DP for Solving MDPs 00:10:00
    • What is Monte Carlo in RL? 00:10:00
    • Monte Carlo Policy Evaluation 00:10:00
    • MC Policy Evaluation in Python 00:10:00
    • Windy Gridworld Evaluation 00:10:00
    • Monte Carlo Control Algorithms 00:10:00
    • Monte Carlo Control in Code 00:10:00
    • MC Control without Exploring Starts 00:10:00
    • MC Control (Code Example without Exploring Starts) 00:10:00
    • Monte Carlo Summary 00:10:00
    • Introduction to Temporal Difference Learning 00:10:00
    • TD(0) Prediction Explained 00:10:00
    • TD(0) Prediction in Python 00:10:00
    • SARSA Explained 00:10:00
    • SARSA in Code 00:10:00
    • Q-Learning Algorithm 00:10:00
    • Q-Learning in Python 00:10:00
    • Temporal Difference Learning Summary 00:10:00
    • Why Use Approximation in RL? 00:10:00
    • Linear Models for Value Prediction 00:10:00
    • Feature Extraction in RL 00:10:00
    • Monte Carlo Approximation 00:10:00
    • Monte Carlo Approximation in Code 00:10:00
    • TD(0) Semi-Gradient Prediction 00:10:00
    • SARSA with Function Approximation 00:10:00
    • Code: SARSA with Approximation 00:10:00
    • Course Wrap-Up & Next Steps 00:10:00
    • Introduction to the Project 00:10:00
    • Working with Stock Market Data 00:10:00
    • Designing the Q-Function 00:10:00
    • Project Architecture Overview 00:10:00
    • Code Walkthrough Part 1 00:10:00
    • Code Walkthrough Part 2 00:10:00
    • Code Walkthrough Part 3 00:10:00
    • Code Walkthrough Part 4 00:10:00
    • Project Summary & Takeaways 00:10:00
    • What’s in the Appendix? 00:10:00
    • 2018 Windows Setup Guide 00:10:00
    • Installing Python Libraries 00:10:00
    • How to Learn Coding Independently (Part 1) 00:10:00
    • How to Learn Coding Independently (Part 2) 00:10:00
    • How to Succeed in This Course (Extended Advice) 00:10:00
    • Course FAQs – Pacing, Background, Practicality 00:10:00
    • Jupyter Notebook vs. IDE 00:10:00
    • Python 2 vs Python 3 00:10:00
    • Recommended Course Order (Part 1) 00:10:00
    • Recommended Course Order (Part 2) 00:10:00
    • BONUS: Discounts & Free Resources 00:10:00
    • Exam of Artificial Intelligence: Reinforcement Learning in Python with Real Projects 00:50:00
    • Premium Certificate 00:15:00
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Yes, our premium certificate and transcript are widely recognized and accepted by embassies worldwide, particularly by the UK embassy. This adds credibility to your qualification and enhances its value for professional and academic purposes.

Yes, this course is designed for learners of all levels, including beginners. The content is structured to provide step-by-step guidance, ensuring that even those with no prior experience can follow along and gain valuable knowledge.

Yes, professionals will also benefit from this course. It covers advanced concepts, practical applications, and industry insights that can help enhance existing skills and knowledge. Whether you are looking to refine your expertise or expand your qualifications, this course provides valuable learning.

No, you have lifetime access to the course. Once enrolled, you can revisit the materials at any time as long as the course remains available. Additionally, we regularly update our content to ensure it stays relevant and up to date.

I trust you’re in good health. Your free certificate can be located in the Achievement section. The option to purchase a CPD certificate is available but entirely optional, and you may choose to skip it. Please be aware that it’s crucial to click the “Complete” button to ensure the certificate is generated, as this process is entirely automated.

Yes, the course includes both assessments and assignments. Your final marks will be determined by a combination of 20% from assignments and 80% from assessments. These evaluations are designed to test your understanding and ensure you have grasped the key concepts effectively.

We are a recognized course provider with CPD, UKRLP, and AOHT membership. The logos of these accreditation bodies will be featured on your premium certificate and transcript, ensuring credibility and professional recognition.

Yes, you will receive a free digital certificate automatically once you complete the course. If you would like a premium CPD-accredited certificate, either in digital or physical format, you can upgrade for a small fee.

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Course Features

Price

Original price was: د.إ2,454.31.Current price is: د.إ75.08.

Study Method

Online | Self-paced

Course Format

Reading Material - PDF, article

Duration

17 hours, 25 minutes

Qualification

No formal qualification

Certificate

At completion

Additional info

Coming soon

  • Share
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