
David Elliott
Data Scientist, Data Engineer
This advanced Nanodegree prepares you to tackle data science at scale. Work with AI best practices, build production-ready projects, and gain the confidence to lead data-driven solutions.

Subscription · Monthly
61 skills
8 prerequisites
Prior to enrolling, you should have the following knowledge:
You will also need to be able to communicate fluently and professionally in written and spoken English.
7 instructors
Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:

David Elliott
Data Scientist, Data Engineer

Antje Muntzinger
Professor of Computer Vision

Nathan Klarer
CEO

Joshua Bernhard
Staff Data Scientist at Marketplace

Jo-L Collins
Senior Lead Data Scientist

Victor Geislinger
Machine Learning Engineer

Matt Maybeno
Principal Software Engineer
The content is great although a bit dated on some topic, and sometimes the videos seems to come from other modules and refer to content not seen in the nano-degree, however overall the experience is good and the exercise helps a lot.
Jun 18, 2025
Great course to understand modern algorithms in RL.
Sep 9, 2024
Considering that to buy this course you need to pay Udacity subscription at least one month (250$), this course is simply a scam: Pytorch codes from 6 years ago! That is, the course is still exactly the same from the day it was released, and today (as of 2024) it is outdated. What's more, in some videos they name certain Git hub repositories that have changed. This appears in the actor-critic methods section, which is literally a man marketing himself and reading the code without explaining it, as if he were reading poems. Generally poor explanations of videos of less than 5 minutes, unless you consult the papers and the book that offers, if you start watching the videos you learn rather little. Very poor explanations of programming codes. Unpractical exercises. You have to solve DL problems from already built environments, that is, the practical part is limited to solve video game type environments that have no real life utility. Anywhere is there an example of how to build your own environment? → NO, Impossible deliverables. If you give me a few GPU hours and I have to build my own models and test infinite hyperparameters how am I going to perform that task, if all I can do is copy a code from the internet that I know works so I don't spend those hours? They give very few GPU hours to solve the problems, and these have a lot to do with launching a model, waiting, changing hyperparameters etc. The only good thing about the course is the papers and github repos it redirects to, which are useful. I mean, you pay an absurd amount of money for some internet links. My first and last course at Udacity :)
Apr 12, 2024
Amazing course with the most advanced knowledge about deep RL, yet presented in so pleasant way, that it was such a great adventure to learn and gain new skills with Deep Reinforcement Learning Course! Thank you very much.
Nov 15, 2023
The course explains even the heavy concepts very easily.
Aug 22, 2023
Elevate your data science career with advanced ML, real-world pipelines & AI best practices. Enroll in Udacity's Data Scientist Nanodegree Program to level up now!

Subscription · Monthly