Udemy – Reinforcement Learning Masterclass 2025-5

Udemy – Reinforcement Learning Masterclass 2025-5 Downloadly IRSpace

Aug 17, 2025 - 02:21 Updated: Aug 19, 2025 - 14:17

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Udemy – Reinforcement Learning Masterclass 2025-5

Reinforcement Learning Masterclass. This comprehensive course covers everything from basic concepts to advanced techniques in reinforcement learning (RL) and is designed for data scientists, researchers, developers, and AI enthusiasts. In this course, you’ll first learn the fundamentals of RL, including agents, environments, rewards, and states. Then, you’ll explore Markov Decision Processes (MDPs), Multi-Armed Bandit problems, Time Difference Learning (TD Learning), and Deep Q-Learning (DQN) methods. You’ll also learn about policy gradient algorithms like REINFORCE, A2C, and A3C, advanced techniques like PPO and TRPO, and topics like model-based RL, hierarchical RL, and curiosity-driven exploration. Other topics include Distributed RL, Meta-RL, Multi-Agent RL, Secure RL, Inverse RL, and Off-Policy Evaluation. Additionally, function approximation, model-based optimization, multi-objective RL, and practical applications in robotics, finance, and supply chain management are taught. By the end of the course, you will be able to solve complex problems using reinforcement learning. This course combines theory and practical exercises to strengthen your skills in this area.

What you will learn

You will understand the key concepts and components of reinforcement learning, including MDPs, policies, rewards, and value functions.
You will implement algorithms such as SARSA, Q-Learning, REINFORCE, PPO, TRPO, SAC, and DQN in Python.
You will use modern libraries like Stable-Baselines3 and TF-Agents to solve real-world problems with RL.
You will implement actor-critic and policy gradient methods using neural networks.
You will understand how to apply reinforcement learning in multi-agent and multi-objective environments.
You will build complete projects from start to finish, such as inventory management, recommender systems, and resource allocation, with RL.

This course is suitable for people who:

This course is for anyone who wants to learn reinforcement learning from the ground up and apply it to real-world problems – whether you’re a data scientist, engineer, researcher, or an advanced student looking to learn RL from both theoretical and practical perspectives.

Reinforcement Learning Masterclass Course Details

Publisher: Udemy
Instructor: Advancedor Academy
Training level: Beginner to advanced
Training duration: 20 hours and 3 minutes
Number of lessons: 85

Course syllabus in 2025/5

Reinforcement Learning Masterclass Course Prerequisites

Basic understanding of Python and Numpy is recommended. Familiarity with probability, linear algebra, or machine learning will help, but not mandatory — the course starts from the foundations and builds up gradually.