Reinforcement Learning beginner to master - AI in Python

Build Artificial Intelligence (AI) agents using Deep Reinforcement Learning and PyTorch: A2C, REINFORCE, DQN, etc.

4.34 (1377 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Understand the Reinforcement Learning paradigm and the tasks that it's best suited to solve.

Understand the process of solving a cognitive task using Reinforcement Learning

Understand the different approaches to solving a task using Reinforcement Learning and choose the most fitting

Implement Reinforcement Learning algorithms completely from scratch

Fundamentally understand the learning process for each algorithm

Debug and extend the algorithms presented

Understand and implement new algorithms from research papers

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Our Verdict

This Reinforcement Learning course offers a solid foundation in understanding RL concepts and algorithms for learners who are familiar with Python libraries or willing to troubleshoot outdated code. While it falls short on supporting beginners, the excellent presentation style—combining theory and practice—makes the learning experience engaging. Enroll if you're comfortable working through potential library compatibility issues in a quest to master Reinforcement Learning using Python.

What We Liked

Covers a wide range of Reinforcement Learning concepts and algorithms
Excellent presentation that balances theory and code implementation
High-quality example code, great for practicing RL algorithms
Clear explanations that break down complexities effectively

Potential Drawbacks

Assumes high familiarity with various Python libraries
Lacks guidance for beginners setting up and using Python libraries
Some Q&A sections are ignored, leaving questions unanswered
Outdated code examples cause compatibility issues with newer software versions