Avis et commentaires pour d'étudiants pour Scalable Machine Learning on Big Data using Apache Spark par IBM

There should be some more exercises for practice.

Would've loved if more practice tests were given

The Course can be made to cover some more basics

Please less math calculus in the quitzzes

Need to be more organized course items

Environment never get set up properly

Good refresh of Apache spark

Video is too blur

très intéressant

.

Content was good even though very basic on statistics, certainly a good intro to Spark. However, final project/quiz was nearly insulting. Code was already written 100%, and most quiz questions were about copy/pasting literal output from pre-written code. Thought a mistake was made at first.

When students follow a course with a serious intent to learn, giving them a final quiz that barely tests their knowledge is a big downer, and makes students feel like they wasted their time learning all this stuff (even though they didn't). Students had proper access to all the code they needed to write 100% of the code themselves for the final quiz. Not sure why everything was done for them in the first place.

If you have some experience with python or ML - it is an easy course to follow but seems not to be deep enough. If you are begginer in these field I do not reccomed the cource.

Not really systematic. The only thing it does: of you have and experience with python and ML it let you taske Spark. But all you skills seems to be not really used. Also the concepts of sparks seems to be hardly touched. I would call the course "Hello world"

if you are a begginner: you will not learn about ML or python. Some concepts are explained on simlpfied level that could lead to misleading.

Tests and actual topic seems to be unrelated

Good day whoever reads this!

First of all I'd like to say thank you for the course. This topic is pretty interesting for me and I move through this course with interest. IF you would update videos according python 3.6++ as in notebooks it would be much easier to learn and get into things. Also final assignment seems a too easy.

Also quality of sound and videos varies from week to week, and sometimes even from lesson to lesson during one week.

Good day and best luck!

The course was presented well by an enthusiastic instructor. The material covered was very good. Unfortunately the course did not offer challenging coding assignments to help the student really embrace and exercise the Apache Spark system. The graphics at times were blurry and hard to read. Suggestion: Maybe incorporate some coding assignments that are graded by the community of students in conjunction with the various tests in place now.

In my opinion, the quality of the videos is not good, and while the teacher explains sharing his display, the display is fog and it is so difficult to see what is doing with the code.

In addition, some classes are recorded from a teacher´s car, I may understand that in some countries it could be usual, but in another one is a signal of non-professional behaviour.

Decent overview of some of Apache Spark's features, but it seems the course team didn't really know what audience to aim for (some of the basic algorithms are reviewed but there's very little about SparkML Syntax, you're just supposed to figure it out). It would be nice to have a more hands-on approach (all the labs are just executing cells, no real exercises)

Its only a part of a longer course. I would have prefered the longer version without getting the feeling of missing half of the story. The final Project did not feel like i did it my self. The answers of the last to questions in the correspondig test where strange (wrong?). Nevertheless I got the feeling that the full course would have been really nice ;)

The Course is complicated to understand for beginners. The introduction and many concepts could be more clarified at a slower pace. It would be better if the instructor could use a bit more time to teach the concepts and explain the concept of the Spark environment in general. Otherwise, the instructor has put a valiant effort.

Some of the content could have been presented more clearly and recorded in the same manner consistently, few items seemed to repeat also while other are not covered well. The code walk thought should have been better explained and with less errors/clarifications which are later explained through video quiz or overlays.

Good for learning the fundamentals of Spark, but unfortunately this course is becoming out of date. Many of the lectures need to be completely re-rerecorded to keep up with the evolution of spark. The quizzes are painfully easy and don't reinforce enough of the code. Needs more coding assignments. All in all, it's OK.

This is a quick, on-point introductory course for Apache Spark, not extensive, since not many industries are going for it, but the necessary concepts like Extract, Transform and Load also know as ETL is explained very well. The instructions are bit scarce, but the notebooks helps a lot. Overall, good!

-Some videos seem outdated, and one of them doesn't have all subtitles.

-The exercises sometimes uses some models or functions not covered in the videos

-I had some issues connecting to the Spark Kernel (it was working before and then stop working. It fixed it self after a few days)

I felt that the course was filled with practicals which was explained very fast and without proper explaination. But the overall content was really good. It must have been more than 4 weeks and with proper explaination on coding part and including more related theories.

i like very much the Machine Learning, but the course was focusing to cover the whole functions,methods,logarithms...

but i was preferred to focus on few concepts and do more practicing on to understand more the course and to make it more beneficial in our job carrier.

I think this is a fine introduction to Apache Spark, but the notebooks don't really require much thought to complete. It'd be nice if they were a bit more instructive. And I'm not a big fan of lecture videos just showing the instructor type the code.