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dhruvp

Hey!

It's a difficult, 9 month program where we cover the following (some of which you mentioned):

- Computer Vision and OpenCV

- Deep Learning

- Sensor Fusion (Radar, Lidar)

- State Tracking with Filters (Kalman, Particle) and Localization

- Controllers

- Vehicle Dynamics

We have come up with this curriculum after talking to the heads of Engineering at Mercedes Benz, Otto, and NVidia at length. In addition, we have an open ended section where students can dive deeper into an area of their choosing.

Like you mentioned, a lot of this is Math heavy, which is why we have applications to enroll. Hope that answered your question!

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Cool, here in the Netherlands I have all the time trouble finding master students that have a thorough machine learning background (https://dobots.nl/hall-of-fame/). There is quite a need for this, also in general autonomous robotics! And there is lower hanging fruit than self-driving cars...

I would be grateful if you provide good (math) fundamentals. It's much harder to understand how things work if you have to search for it yourself. Suppose you've never heard about a spark (https://en.wikipedia.org/wiki/Spark_(mathematics)), a Hilbert space (https://en.wikipedia.org/wiki/Hilbert_space), Metropolis-Hastings (https://en.wikipedia.org/wiki/Metropolis%E2%80%93Hastings_al...), or a Dirichlet Process (https://en.wikipedia.org/wiki/Dirichlet_process), then it's not so easy to find such concepts and understand their significance.

(1) If you need some help, you can find me here. I'm currently playing with MCMCs in nonparametric Bayesian methods that adapt to the structure in the real world. It is a waste to sample everything. For examples aisles in a supermarket have structure to them. In the "visual grammar" of the supermarket, they are aligned with each other. MCMC that can encapsulate this type of grammar will mix much faster.

(2) If you find a pupil interested in the combination of transfer learning and deep learning, feel free to refer to me. I'm not interested from the viewpoint of domain adaptation, but from the viewpoint of robotic communication.

Do they have to be Masters students?

Yes, I found out that the topics are typically hard enough that around 9-10 months are spent on them, typical graduation time in Europe. Of course, it also gives me the opportunity to see how someone works, rather than relying on a short application process. :-)

Some big omissions there:

- Hard real-time

- Fault tolerance

- Safety engineering

- Human factors analysis

The stuff that kills people. An automatic driving project should have someone from avionics design on board.

Does Udacity offer programs for those lacking _(partially or entirely)_ in the math(s) required for these types of courses? Ie, to bring them up to speed?

I'm not sure if Udacity is even interested in teaching these types of courses, fwiw... though, i know Khan has lots of math courses.

Hey!

We do have a few math courses such as our Intro To Statistics class (https://www.udacity.com/course/intro-to-statistics--st101) and our Linear Algebra class (https://www.udacity.com/course/linear-algebra-refresher-cour...) but I'd still recommend Khan Academy or MIT OCW's math offerings. The 18.06 class on OCW by Professor Strang is really awesome in particular.

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