學生對 IBM 提供的 Scalable Machine Learning on Big Data using Apache Spark 的評價和反饋

Unfortunately, there seems to be quite a few errors in the course. The only skills that you can actually take away is how to use Apache Spark. The machine learning and evaluation metrics explained in this course are riddled with errors. When writing to the teachers the only thing they say is they are checking on it and will get back to you and never do. I usually really like the IBM courses but this one was by far the worst MOOC I have taken so far.

One of the worst courses I ever had.

1 - The whole thing seems rushed. A lot of mistakes!

2 - Confusing slides and exercises.

3 - Useless quizzes that provide no additional benefit to the learner.

4 - Uncompleted transcripts under the videos.

I do not recommend this course. Unfortunately, I have to complete it for a specialization, otherwise, I would have abandoned it.

Out of date and confusing examples. Watson studio is hard to setup. Instructions were misleading. Incorrect information was taught. Accent sometimes hard to understand. Testing did not directly relate to course material and required external study. Tests within instructions videos did not pop up at natural intervals. Overall a disappointing experience.

The course is definitely one of the worst i had in coursera. Many issues with the sound (week 1) which in combination with the very hard accent of the tutor becomes unbearable for the first 2 weeks at least. The concepts are not explained enough. If you really want to learn choose something else.

The course is based on a previous version of IBM Watson platform that makes too many slides outdated. Too much time is dedicated to the definition and computation of basic statistical moments. The same information about Apache Spark is published on the project's website.

The course has been forcefully put inside the IBM AI Engineering Professional Course, and does not fit in. The course instructor fails to explain the details in an effective way. Overall this course is not designed to be a part of this specific specialization.

Maybe I do not have knowledge about Python, but a lot of things were not understandable for me. In addition, parts of the course are still shown in an older, out-of-fashion version of Watson. The shown code is not working in todays version

This course and assessment method is not standard enough. It should have more practical exercises such as RDD programming, ML, SQL. Course project should have related to developing mini big data application with RDD to ML prediction.

The course should be reorganized. The video are taken from different courses and is not fluid follow it. There is very little in programming with functional programming. There are many concepts but not well explained. Not advided!

The course teaches important concepts and skills on how to scale your machine learning algorithms - but it is in a desperate need of an overhaul to fix the numerous errors in the videos and workbooks.

Did not like it that much, I´m not clear about spark and big data use cases for ML. The themes were variated and did not follow a line or path of learning.

Not clear at all.

A lot of things are not explained, or explained in a confusing way. I learn more by researching what things meant than from lectures

I dont like the instructor very much. I feel like his explanations are not the best and everything was just too fast.

It's very difficult for a beginner (like me) to understand the whole science behind the concepts in Apache Spark

The content is quite old and full of mistakes. It would be great if the course material quality is improved.

Explanation not satisfactory and exercise also not so good.

too much issue in setup all these exercises.

focus too much on practical skills than the balance of concepts and implementations

confusing to follow

It was fine, but i couldnt understand clearly what the instructor want to explain.

The course should give more in-depth assignments and also more explanation.

There is a lot of audio problem and content is also not updated.

This course needs more spark towards the student.

Thanks.

Videos are not informative.

A lot of errors in lecture.

So many errors in the codes. Especially the ones the instructor is showing us in lecture (his files run on python 2.7 and i'm running on python 3.6- has not updated some programs to run on python 3.6 with spark 2.3). He doesn't specify which file at the beginning of the video, nor does he have a link to the sample code he is showing us, nor does he specify which file to insert a spark session and to where can we find that specific file in GitHub. It's a huge confusion for a person who has zero programming knowledge and It took me a lot of time to fix the errors in the codes to get back on the lecture. I am utterly disappointed with this section. Didn't have any issue with the last session of this course. I wasted a lot of time. I'm utterly disappointed with this course.

However I must appreciate his lecturing is excellent. I was able to fully understand the theoretical part he explained. I did however fail to quickly understand the programming aspect due to multiple errors in the code.