My name is Dhruv and I work on the AI programs here at Udacity. If you have any questions, feel free to ask them here or email me at dhruv@udacity.com. I'll do my best to answer everything! You can see our curriculum in depth here: https://medium.com/udacity/deep-learning-nanodegree-foundati...
2. I watch Siraj's videos. Although they are fun and useful, they are very short and resemble a recipe in a cookbook (no offense intended). Is the course going to be the same as videos? Or is it going to be discussing all the necessary mathematics/statistics?
3. I couldn't find detailed information about the instructors' background. Are they able answer questions from the deep learning book or Sutton&Barto, if one were to read them alongside the course?
1. We'll provide instructions to use AWS (65 cents an hour) and are working with AWS to get students credits. We've done this in the past so there's a decent chance we get this but no guarantees yet.
2. The course is going to be Siraj's videos supplemented with additional content to go deeper into the math/statistics and to actually do problem sets and projects. So Siraj is meant to be the starting point from where we go deeper.
3. Mat Leonard will be the main instructor and did is PhD in Physics and Statistical Neuroscience at Berkeley. He's done his fair share of reading from books in the field and will be able to answer your technical questions.
So we require AWS for sure to complete this course right? Can you suggest the system configuration needed for this course?
This course will focus primarily on TensorFlow. We're doing so because, at the moment, it's the most popular Deep Learning framework and provides you enough flexibility to explore some of the newer network architectures we focus on towards the end of the program.
Also will there is new materials added periodically or is this for a short duration of time frame?
You have 6 months in total to finish all the content. Siraj is also posting some segment of the content for free on YouTube for everyone to see. The new material is added weekly!
I'd say that covers a larger breadth of Deep Learning than the Self-Driving Car Nanodegree program. For instance, this program will cover Recurrent Neural Networks, Reinforcement Learning, Autoencoding, and other Deep Learning applications not covered in the Self-Driving Car Nanodegree. In the Self-Driving Car Nanodegree, we primarily focus on Deep Learning applications in Computer Vision. Here we'll cover applications in speech, computer vision, game-playing and other areas.