Excellent course! All the explanations are quite clear, a lot of good quality information provided from amazing teacher. Additionally, response times for any question is very fast.
Really really REALLY enjoyed this course! The instructor does a masterful job of going from simple examples and building up complexity in a very logical and thorough way.
por Miele W•
Again a nice course that introduce you on Apache Spark Usage. Just a little suggestion, if you could insert a little tweak on how pass from spark to pandas and vice versa.
por Dhivyarupini R•
Teaching was clear and understandable. Only feedback would be I hope the lab work would be more hands on because I'm worried I don't pick up the concepts unless I type them out.
por Ihsandi D•
Depending on the student, this can either be an easy or a difficult course. Some parts needs update, and it would be great if there are more explanation on the algorithms.
por Robert v d V•
Nice introduction to Big Data processing, No coding skill required. A little more focus on the theory would be nice as the Python coding exercises are a little redundant.
por Giorgio G•
Great tutorial overall.
Room for improvement: Fix the differences int the definition of kurtosis and skew between vide, test, examples (preferable the scipy definition).
por Zaheer U R•
It was a very interesting and skillful course. Thanks to IBM and Coursera for such a wonderful course. Special thanks to Mr. Romeo Kienzer for explaining it so well.
por leonardo d•
There are some issues with the normalization of the distribution moments. Everything else is good material to learn how to use apache-spark for the first time.
por Julien P•
Great notebooks. But the videos are getting old and are a bit obsolete compared to the contents in notebooks. I would have also appreciated more theory.
por Chokdee S•
Learning material is pretty good for getting started with Apache SparkML. Everyone who leaps into Scalable Machine Learning this is one of your choice
por Brandon C•
I found this course incredibly beneficial. Moving forward, I would like to see a bit more explanation of concepts and few extra workable examples.
por Stefan W•
Course was nice and avoided peer-graded assignments (which I appreciate) but code was written in Python 2 which led to un-maintained code.
por Shahtab A K•
In some videos, it shows one thing in the video and then there is a prompt to follow another one. It gets a little bit confusing there.
por Itamar A T•
I found difficult to understand the concepts, for sure I must have to review the class.
Thanks for the dedication in helping us.
por Shashank S•
for the last assignment we should have got the opportunity to code in the notebook instead of just running it and reporting results.
por Sarath C G K•
He has good knowledge. Though his language is ok , He covered very important topics in very short span of time with high quality
por Lawrence K•
Nice course with real details and opportunities to practice. We just need some more private study to cement skills learnt.
por shanmukha y•
I felt the week 3 and 4 were rushed a bit. But everything else was well done. It was like a well defined "pipeline" : )
por Stephane A•
Nice course. I really understand big data and how to manipulate data in data centers. I can use better Apache Spark.
por No O•
Explanations could be a little more detailed. Felt like I was missing chunks of information while watching videos.
por yan l•
very systematic way to learn ApacheSpark (esp pyspark). It would be helpful to include more hands on excercise
por Daxkumar J•
This course gives you a basic idea behind the pyspark. If you are a beginner so this course for you.
por JOSE J M C•
Instructor pronunciation is not the best for someone who are not usually listening explain so fast.
por Jochen G•
Cool course with a slow paced start and then interesting examples to work with Apache Spark ML.
por Anaísa S•
Good course, but coach's English is poor and many corrections are made during presentations
por 126_YASH K•
Overall its an excellent course but I think more programing exercise should be there.