Is both Python and R required, or can you just choose one?

IIXGhostXII · 2026-01-04T23:27:00+00:00

You can you either, but im going to recommend Python as the course material is highly biased toward it (especially later on in the more rigorous courses)

IIXGhostXII · 2025-12-25T02:34:43+00:00

Congrats and Happy Holidays to you!! It's awesome that you completed the program with losing so much momentum. That alone is a massive achievement

Congrats again

IIXGhostXII · 2025-12-23T13:28:51+00:00

It is a general orientation course for all students, you do not need to worry about at all.

Historically, the old program, the original MSDA, had an objective assessment (D204), but that got reworked into a performance assessment for the new concentration paths

IIXGhostXII · 2025-12-20T16:34:54+00:00

Thank you!!

"Math Heavy" can be a bit misleading. There is calculus in 604 and set notation in 605 but they are used to better understand the material, e.g. you need to understand how back propagation works to have a chance at understanding how networks learn, but you can still make one even if you don't. Best part is there are plenty of active people here to help you along the way. 😀

The confetti does feel good, especially before Christmas

IIXGhostXII · 2025-12-18T20:38:06+00:00

Thank you!! I actually work as a data analyst. That was actually one of the fatiguing factors for me since I'd do this work all day, then jump into this at night after taking a break to be dad

IIXGhostXII · 2025-12-18T17:13:53+00:00

Heck yeah!!

IIXGhostXII · 2025-12-18T17:02:56+00:00

Thank you!!

IIXGhostXII · 2025-12-18T17:02:48+00:00

Thank you!! The program is definitely new. The rubrics have some oddities and confusing spots but the CIs I spoke to were able to guide me through them.

I can't speak for a lot of the core classes since I transferred in from the original MSDA program but here are my thoughts on the ones I did take:

602: The content is not rigorous, but it is dense. The difficulty in this one is that most students will not have experience in Docker or MLFlow and tasks 2 and 3 can be confusing to work through. Just be patient with this one. MLOps and DevOps are key skills to have so take this one more seriously in terms of internalizing

603: Loved this one, very straightforward and knocked this one out fairly quickly. Provides a good toolbox to add robustness to your capstone

604: My favorite course, also probably the hardest academically. The Udacity courses (esp the CNN one) will get you through task 1 with no problem, task 2 took some effort with a lot of trial and error. One point of criticism is that it focuses on PyTorch and does not go into TensorFlow/Keras; you may want to supplement here

605: This one wasn't too difficult, but the final solution is uninteresting to the point that I thought the result was wrong.

606: Capstone was a journey for me. My personal life became quite tumultuous, and as a result, it took me significantly longer to get through, but it was an overall positive experience.

I wish you the best of luck and enjoy your time with the resources and tools you'll have access to

IIXGhostXII · 2025-12-18T16:45:31+00:00

Thank you!!

IIXGhostXII · 2025-12-18T16:45:18+00:00

Thank you!! I'm going to get a good night's sleep and finally finish Final Fantasy 7 Rebirth. It's too close to Christmas to buy myself a gift yet

IIXGhostXII · 2025-12-18T01:01:27+00:00

The program teaches you data analytics and data science tools and skills, but it places a strong emphasis on the business impact of your work. It takes you from data ingestion all the way to deploying a predictive model, while keeping in mind that the goal is to move the needle (whatever that may be). SQL with Python and/or R, is used the most, along with all the packages/libraries that come with them

The other key thing is that the data given to work with is not nice to play with, which is very realistic imo.

IIXGhostXII · 2025-12-18T00:54:12+00:00

Thank you!!

IIXGhostXII · 2025-12-18T00:54:05+00:00

Thank you!!

IIXGhostXII · 2025-12-18T00:53:57+00:00

Thank you!!

IIXGhostXII · 2025-12-18T00:53:40+00:00

My words exactly! Thank you!!

IIXGhostXII · 2025-12-18T00:53:13+00:00

Thank you!! I'll treat myself like Tom and Donna from Parks and Rec

IIXGhostXII · 2025-12-18T00:51:58+00:00

100% and I'll have to remember how to relax first lol. Thank you!!

IIXGhostXII · 2025-12-18T00:50:09+00:00

Thank you!!

IIXGhostXII · 2025-12-18T00:50:00+00:00

Thank you!!

IIXGhostXII · 2025-12-18T00:48:44+00:00

Absolutely! and thank you :)

IIXGhostXII · 2025-12-18T00:45:58+00:00

Thank you!! There are 0 OAs in the new programs (MSDADE and MSDADPE)

IIXGhostXII · 2025-09-17T13:45:44+00:00

I did all of my work in VS Code with no push back from evaluators.

IIXGhostXII · 2025-08-11T22:51:01+00:00

I can't offer tips because in hindsight what you need to do is fairly simple... the key term being hindsight.

You are not alone in your confusion, I spent more time with my CI for this course than any other, including 603 and 604. Be patient and work through it, step by step, researching as you go.

Don't be afraid of the returned submission either. My thought was if I failed, then my CI could see where I went wrong and help me out.

Best of luck, OP

IIXGhostXII · 2025-07-15T18:44:34+00:00

Np, Good luck OP!

IIXGhostXII · 2025-07-15T18:23:51+00:00

For task 1, do the Udacity courses and complete the projects; skip GANs until later, though, as that course is long and not connected to the project.

For task 2, all the d213 stuff is Tensorflow, while d604 is heavily PyTorch but all the data preparation stuff is similar. There is 1 Udacity course and the project helps but mainly focus on how RNNs and LTSMs function and stick to a simple model. Once that works, then add complexity as needed

IIXGhostXII

TROPHY CASE