Nice subjects notebooks could be more in-dept

too easy, programming part too stupid

seems it is not well prepared

too simple

not advanced

it's not enough clear

Extremely advanced.

Low level

The concepts behind the use of Spark are not explained very well. Otherwise, the content is very simple. I thought the value of this course would be in learning Spark by applying it to concepts that I already know well, but the course didn't do a very good job of thoroughly teaching Spark concepts. I don't really think this course is appropriate as part of an "Advanced" data science series. The material is extremely basic. I didn't get much out of this course. I hope the others in the series are better.

N​ot very good. There is no logic in the lectures and the exercises. I have been a reputable pure mathematician for many years. Taught several linear algebra courses. But when I hear the "linear algebra" taught by Romeo Kienzler I am deeply confused, completely don't know what he wanted to say. The exercises on "linear algebra" are equally bad, confusing, with no logic.

A disappointing amount of the material presented is out of date (e.g. what environments to use, Watson vs 'Data science experience' )--while fine for some cases, it too frequently borders on intrusive at best to desperately opaque at worst. Clarity of presentations could also be greatly helped. Perhaps focusing more on the why? and so what? aspects would be helpful

The explanations are not clear enough- the rational for using spark is not clear enough (missing context explanation, etc)

missing written lecture notes (in bullets- summariezed)

It would be helpful if the lecture text would be integrated in the video itself and not below the video presentation- harder to follow

Interesting material, but i don"t feel i"ve learned how to actually use spark on my own. Most of the code was already in place during the assignments and i just had to add some minor easy parts. Kept some nice noted though and will revisit this in the future.

Not recommended course for an intermediate level of Statistics and ML. I had the impression it will be focus on pyspark and apache, but it turned out to be on ML topics.

The videos are fuzzy, extremely outdated, and don't match up with the actual projects. I couldn't pay much attention to them. Projects were good though.

The material was outdated, and the programming assignments were more appropriate for novice learners, rather than professionals is the field.

Romeo does a very good job of explaining things!

However, the programming assignments are too easy to learn anything from.

Meh. Not the best one. Videos are hard to watch and not very clean instructions. I'm going to try a different course.

Both exercises and programming tests are too easy. It should be real programming instead of filling in the blanks.

very simple. homework not challenging enough - just repeating the demos almost exactly.

The course content is not well structured and at times very confusing.

Very basic and Spark exercises are too easy to learn useful skills

Not really fundamental. Beginner will have difficulty to learn.

Big data materials are less discussed specially coding sections

The course feels old now. Not much interactive.

Very good topics very not very good instructors