Value-Based Methods

Course

Apply deep learning architectures to reinforcement learning tasks. Train your own agent that navigates a virtual world from sensory data.

Advanced

2 weeks

Real-world Projects

Completion Certificate

Last Updated October 7, 2024

Skills you'll learn:

Value-based reinforcement learning • Prioritized experience replay • Deep q-networks • Double deep q-networks

Prerequisites:

Reinforcement learning fundamentals • Deep learning framework proficiency • Neural network basics

Course Lessons

Lesson 1

Study Plan

This lesson covers the study plan and prerequisites for this course.

Lesson 2

Deep Q-Networks

Extend value-based reinforcement learning methods to complex problems using deep neural networks.

Lesson 3 • Project

Project: Navigation

Train an agent to navigate a large world and collect yellow bananas, while avoiding blue bananas.

Taught By The Best

Dana Sheahen

Content Developer

Dana is an electrical engineer with a Masters in Computer Science from Georgia Tech. Her work experience includes software development for embedded systems in the Automotive Group at Motorola, where she was awarded a patent for an onboard operating system.

Arpan Chakraborty

Instructor

Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.

Kelvin Lwin

AI | Knowledge Architect

Kelvin had taught in US Academia and Industry within highly technical subjects of CS and AI/DL for a decade. He expanded into building AI Fullstack in China to have a broader global perspective for 3 years. Now he is combining AI, Empathy & Ethics informed by his 18 years of meditation to build new Educational AI for all.

The Udacity Difference

Combine technology training for employees with industry experts, mentors, and projects, for critical thinking that pushes innovation. Our proven upskilling system goes after success—relentlessly.

Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

Gain proven experience
Retain knowledge longer
Apply new skills immediately

Top-tier services to ensure learner success

Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.