Udacity — Deep Reinforcement Learning Nanodegree Program Syllabus

Published in

AltoTech

3 min readOct 6, 2018

Become a Deep Reinforcement Learning Expert

Before You Start

Educational Objectives: In this program, you’ll learn the theory and practice driving recent advances in deep reinforcement learning. This program will cover the latest techniques used to create artificially intelligent agents that can solve a variety complex tasks, with applications ranging from gaming to finance to robotics. With the practical skills you gain in this program, you’ll be able to understand the most cutting-edge research papers, and build an impressive portfolio containing your own coding implementations.

Prerequisite Knowledge: In order to succeed in this program, we recommend having significant experience with Python, and entry-level experience with probability and statistics, and deep learning architectures. Specifically, we expect you to be able to write a class in Python and to add comments to your code for others to read. Also, you should be familiar with the term “neural networks” and understand the differential math that drives backpropagation. If you feel you need to add to your Python and statistics skills, we suggest our Machine Learning program. If you’d like to learn more about neural networks and backpropagation, consider our Deep Learning program.

Length of Program: The program is comprised of 1 term, lasting 4 months. We expect students to work 10–15 hours/week on average. Make sure to set aside adequate time on your calendar for focused work.

Instructional Tools Available: Video lectures, Jupyter notebooks, personalized project reviews.

Contact Info

While going through the program, if you have questions about anything, you can reach us at drlnd-support@udacity.com.

Nanodegree Program Information

This program is designed to enhance your existing machine learning and deep learning skills with the addition of reinforcement learning theory and programming techniques. This program will not prepare you for a specific career or role, rather, it will grow your deep learning and reinforcement learning expertise, and give you the skills you need to understand the most recent advancements in deep reinforcement learning, and build and implement your own algorithms.

The term is comprised of 4 courses and 3 projects, which are described in detail below. Building a project is one of the best ways to demonstrate the skills you’ve learned, and each project will contribute to an impressive professional portfolio that shows potential employers your mastery of reinforcement learning and deep learning techniques.

Length of Program: 160 Hours*
Number of Reviewed Projects: 3

The length of this program is an estimation of total hours the average student may take to complete all required coursework, including lecture and project time. Actual hours may vary.