So far the questions and quizes seem unrelated to machine learning. The videos are poorly set out, with breif explanations and the whole thing seems rushed.

Apache spark is great and powerful but the lectures are not clear and long.

Trully disappointing!! Waste of time and money. Really poor video material and exercises.

I definetelly dont recommend this course!!

Too superficial. The python example codes are very cryptic and not very well commented. The programming videos are very difficult to follow because the instructor is literally reading the code instead of explaining it.

I am quite disappointed by this course, which could be greatly improved.

Here are a few remarks :

1) Half of the course is about basic statistical distribution analysis : always nice to learn about that, but it has nothing to do with spark and is more general datascience knowledge

2) Most of the topics are just mentionned but the instructor, which never goes into explaining interesting details. It's always "don't worry if you don't understand that, it doesn' matter". Well, actually if it's only to learn basic stuff I don't need coursera...

3) In several videos, the instructor just records himself coding with spark for several minutes. How boring ! At what point do you think this kind of video is of any interest for your student ? What are the practice lab for ?

4) The quizz are annoying ! Not that they are "easy" but most of the answer of the questions are either ambiguous or not related to the course and must be found elsewhere

5) The final quizz is a joke and you just have to run a notebook and then copy/past the answer. Even there, some question are ambiguous : you are asked to change a model and then "compare the models", but which one ? The one we changed or the initial one ? And so one.

In conclusion, I learn some things and practice a bit apache spark with this course, but 90% of what I learned come from other sources than coursera... I put excellent marks on other courses so don't think I am just ungrateful.

Video is outdated. The course material is not structured properly. Lack of explanation on the code. The code reference is confusing.

Demotivating course, the worst I studied on Coursera. If not "AI Engineering" path I would have dropped it

a very low quality course, not recommended. 质量很差的一个课程，讲师带严重口语也就算了，连英文字母有时候都缺失或者对不上，作业质量也很差，不建议上，看的累

Obsolete presentations with low quality of explanations. I would not recommend this course to anyone.

Horrible

The course is interesting but I think a few things could be improved.

For instance, some code examples from the videos are outdated because of a newer spark version. The video was edited to mention that the github repo was updated but I was unable to find the updated code.

One (maybe more?) of the videos was done in a car; It makes the whole thing feel unprofessional even though the teacher's skills far exceed the requirements for teaching this course.

As others have mentioned, the teacher's accent can be a bit difficult to understand at times but to me, this does not affect the quality of the course. The teacher always seems interested and is smiling most of the time which might seem unimportant but it still sets a positive mood for the lectures which is great.

All in all, the course is interesting and it provides a good introduction to Machine Learning using Apache Spark.

Really interesting content

Unclear coding explanations

Limitations with the free access in IBM Watson Studio

the accent of the instructor was very hard to understand him during explanation but he was good instructor at all

Very primitive tasks

There should be more details about Apache spark and some examples

For a intorductory course it is very good. Do not expect anything too advanced.

A very good course and will recommend it for anyone who has Apache Spark experience and wants to get an introduction to ML lib and machine learning in Apache Spark, the assignment submissions need some work but other than that a very good introductive course.

Course can be improved by focusing more on ML algorithms.... Explanation of GBT and Random Forest was not provided. But they were used.

The Videos/tutorials need to be updated for the new pyspark. Some are still using python 2 which reaches end of life in a month!

Very Good, but I think the course needs more challenging exams

It is in general a nice introductory course to see what ApacheSpark means and what it can do but the course is a bit outdated with a lot of patch notes on the slides telling you something is not the way it is shown, the production of the 2 first weeks is bad (bad sound and unintelligible slides).

I think IBM should update it and maybe make it more challenging 'cause you barely get hands on experience, the graded quizzes are pretty easy and not much of your grade is related to practical exercises.

In very simple and crisp way a lot of details are covered about Apache Spark. Very good way to start.

Great tutor, he loves to keep things simple and to the point. Loved the course.

Too high-level, mismatch between code and Watson setup Video vs working notebooks, teacher does not explain basic building blocks re RDD and DF what is the difference, when each of them should be used, complicated subjects have videos by 3-5 minutes, absolutely simple exercises. What is the basic difference with sckitlearn and how different work should be organized. NO any supporting materials, some code is not working, errors in videos with clues "don't do this"... Not serious approach for building this course. Sorry

I don't feel I've learnt much in this course and I certainly can't recommend it. The videos are of poor quality and the selection of examples is bad (use real use cases instead of explaining basic statistics). The quizzes are way too easy and require no problem solving at all. This course needs being redesigned from scratch.