Amazing course! Thank you!

Excellent Course!

Very good course!

excellent course

Excelente Curso

detailed course

Great course !

great trainer

great course

Good Course

Masterpiece

Good course

Awesome :)

Excellent

fabulous

Good

good

TLDR for those who don't want to read through all of that, the course gives a shallow entry into the data engineering part of machine learning. I wished they would make the course more challenging, so that we would learn more.

For people considering the IBM AI engineering specialization and this course, I would say that it is a very good introduction. For those looking for a more in-depth approach to ML and DL, then this course isn't going to hit those areas. Regarding this course specifically, they did a good job explaining the concepts well. I would have preferred if they made the course proejct a lot less hand holding. They essentially give you the jupyter notebook with all the ETL procedures done, and you change like 4 variables, which isn't really intellectually stimulating or challenging. I understand that the course is meant to be an introduction, but I think asking us to do the ETL by ourselves with less rail guards would teach the students a lot more. Like I would say I learned more about Apache Spark and functional programming from the 2nd module quiz than the course project, because the quiz had us writing the code ourselves, and I had to learn and debug functions on my own.

I can't fault Romeo for his enthusiasm and engagement in the forum, and nor do I think his accent is a problem. I can say I learned something from this course, but there are a few negatives

-- Some parts appear unprofessional. This includes the initial videos filmed in the car, the prompts stating that parts are out of date, and the on-the-fly coding in the week 3 and 4 videos

-- The course is initially jargon heavy, but it is pitched at quite a low level otherwise. There is a lot of hand-holding, for the final project you make two alterations to the code already supplied and then copy and paste the results. It would benefit from a review of the didactics.

-- I would have loved to have had more opportunity to play with the data. Why not a tutorial on using SQL or data cleaning? Why not more on the application of the ML tools? There's a definite feeling of being in a sandpit and not being allowed out.

That said, I now have experience with ApacheSpark and I understand how to use it to implement some ML methods, which is good.

The content that is taught was actually satisfying, however, it is obvious most parts of the videos were outdated either due to the fact that they are for another course or they were simply not organized from the beginning. In addition, it would have been awesome If the instructor explained the codes more. I feel that I have learnt the basic idea but I need further self-study to make sense of everything we have covered in terms of the coding.

I enjoyed this class. I worked with Spark a few years ago, but wasn't aware of Pipelines and Parquet. The incorporation of these concepts into the course was useful. The instructor is engaging, but speaks quickly sometimes and there are some translation challenges with his accent. I found myself reading some of the material because i had trouble understanding what he was saying.

I would like to thank Romeo for teaching me. I apologize to rate the course at 3/5. I did like the course in general but I missed the practice of it. The methodology process did not help me to learn the practice. I scored better in most quizes on the first attempting while I could not guess how the code are written. I wish I did learn to interpret or rewriting the code

Regards

Its a nice course and good way to start Apache Spark.But I feel its a bit too fast as well as too high level for those who are pure machine learner and deep learner practitioners on jupyters and colabs,they are gonna find it bit tough and programming part will go over the head.So Goodluck.

But its a nice way to start learning a fascinating technology of Apache Spark.

I really enjoyed this course, I think despite this it requires a review to make it more consistent. One thing that would have made it better for me. Would have been to have the jupyter notebook matching exactly the video so I could have worked on them in parallel... Thanks very well build course, it really gives a good base to start using Apache-Spark ML

The material presented in the course is important for everyone looking to go into the Data Science or Machine Learning fields, but some of the examples in the earlier chapters use Python 2 and have not been updated to Python 3. The learner has to go hunting themselves in the forums for official posts on how to fix these error (they were there).