Professional Course

Fundamentals of Deep Reinforcement Learning

edX, Online
8 weeks
75 USD
Next course start
Start anytime See details
Self-paced Online
8 weeks
75 USD
Next course start
Start anytime See details
Self-paced Online
Visit this course's homepage on the provider's site to learn more or book!

Course description

Fundamentals of Deep Reinforcement Learning

This course starts from the very beginnings of Reinforcement Learning and works its way up to a complete understanding of Q-learning, one of the core reinforcement learning algorithms.

In part II of this course, you'll use neural networks to implement Q-learning to produce powerful and effective learning agents (neural nets are the "Deep" in "Deep Reinforcement Learning").

Upcoming start dates

1 start date available

Start anytime

  • Self-paced Online
  • Online
  • English

Who should attend?


  • Requirements:

    • Proficiency with Python
    • Functions, classes, objects, loops
    • Basic familiarity with Jupyter notebooks

Recommended Prerequisites:

  • Basic probability
    • Sampling from a normal distributon
    • Conditional probability notation
    • \mathbb{E}E - expectation
  • \SigmaΣ - the summation operator

Training content

  • Introduction to Reinforcment Learning
  • Bandit Problems
    • Epsilon Greedy Agent
  • Markov Decision Processes
    • Episode Returns
    • Returns and Discount Factors
  • The Bellman Equation
  • Iterative Policy Evaluation and Improvement
  • Policy Evaluation and Iteration
  • Dynamic Programming
  • Q-Learning and Sampling Based Methods
  • Monte Carlo Rollouts vs. Temporal Difference Learning
  • On-Policy Learning vs. Off-Policy Learning
  • Q-Learning
  • What's Next

Course delivery details

This course is offered through Learn Ventures, a partner institute of EdX.

2-6 hours per week


  • Verified Track -$75
  • Audit Track - Free

Certification / Credits

What you'll learn

  • The theoretical underpinnings of Reinforcement Learning ("RL").
  • How to implement each piece of theory to solve real problems in Python.
  • The core RL formula: The Bellman Equation
  • The Q-Learning algorithm, as well as many powerful improvements.
  • Enough to prepare you for implement Reinforcement Learning algorithms using Deep Neural Networks (Part II).

Each concept is presented with a video overview, and detailed Jupyter notebooks covering each aspect of theory and practice.

Contact this provider

Contact course provider

Fill out your details to find out more about Fundamentals of Deep Reinforcement Learning.

  Contact the provider

  Get more information

  Register your interest

Country *

reCAPTCHA logo This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
141 Portland Street
02139 Cambridge Massachusetts


edX For Business helps leading companies upskill their labor forces by making the world’s greatest educational resources available to learners across a wide variety of in-demand fields. edX For Business delivers high-quality corporate eLearning to train and engage your employees...

Read more and show all training delivered by this supplier