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

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Good for learning the fundamentals of Spark, but unfortunately this course is becoming out of date.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Some links is outdated during the course materials. Make sure you update all lib for use in python, such as pyspark. I would say you need a lot of prerequisites to understand all the content and mathematical terminology. Could have been better recordings with more engaging slides and information

-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.

The course material seems to be copy and pasted together from other courses and the versions/classes/functions of the software have changed compared to videos and assignments. Nevertheless I got a first impression on how to work with Apache Spark/pyspark hands on.

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.

The course material was clear but we are never really given any challenging practice exercises to do. The "project" at the end was litterely just running prewritten code - it would have been better if we got to write the code on our own.

It seems that the course is not updated for some time.

What is described in the videos not always applies to the exercises.

Some mistakes are corrected with labels on the video.

In general the quality of the materials is not great.

Its a good course but it duplicated content from the previous course in this specialized certification. Also speed for writing code is too fast in video. But some APIs and exercises are really good.

Overly, It is a well structured and oriented course, especially the practice part. However, the lectures could have been improved and made clearer. Thank you for all your efforts.

The objectives on each class were not clearly defined, and the videos have a lot of errors that are partially corrected but will be good if the content of the course is reviewed.

Lectures video and practice seems not consistent. Some of the contents in the video needs to be updated, since the interface has changed in IBM studio.

Tutor was definitely knowledgeable, but i felt the course was more like a code review and more emphasis should be given to teaching/explaining.

The course teaches the very basics in a pretty simplistic manner. I think both videos and labs could be more descriptive and illustrative.

Very precise examples of parallel process to make predictions but may be not as demanding as other courses. The exercises where too easy.

Good introduction to Spark, but very little playing around with ML.

Also, the UI for IBM Watson keeps changing and is really frustrating.

This course is outdated, and there are a lot of errors in the presentation.

I think most of the videos in the course need to be updated.

Quite difficult to understand, since the videos have plenty of errors and the tutor goes really fast with no explanations some times.