Udemy – Practical Reinforcement Learning for ML Engineers

Reinforcement Learning (RL) is one of the most powerful areas in machine learning — but also one of the hardest to learn. Most RL courses are either too theoretical or too shallow.

Note: This course is taught in Arabic (with English technical terminology).

## What makes this course different:

• Intuition-first approach: we start from supervised learning and build up to RL
• Hands-on implementation: all algorithms are implemented from scratch
• Practical focus: you will work with real environments using OpenAI Gym
• Covers modern topics like RLHF (used in fine-tuning LLMs)
• Includes GitHub repositories for deeper exploration and experimentation

## What you will learn:

• Understand the intuition behind reinforcement learning and how it differs from supervised learning and imitation learning
• Implement REINFORCE, Actor-Critic, PPO, and DQN from scratch using PyTorch
• Use OpenAI Gym to train and evaluate RL agents
• Understand key RL concepts: MDPs, value functions, policy gradients
• Learn how RL is used in fine-tune large language models (RLHF, PPO, DPO)