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.
创建者 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.
创建者 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.
创建者 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.
创建者 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.
创建者 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).
创建者 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.
创建者 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.
创建者 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.
创建者 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
创建者 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.
创建者 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.
创建者 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.
创建者 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.
创建者 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.
创建者 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
创建者 Lawrence K•
Nice course with real details and opportunities to practice. We just need some more private study to cement skills learnt.
创建者 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" : )
创建者 Stephane A•
Nice course. I really understand big data and how to manipulate data in data centers. I can use better Apache Spark.
创建者 No O•
Explanations could be a little more detailed. Felt like I was missing chunks of information while watching videos.
创建者 yan l•
very systematic way to learn ApacheSpark (esp pyspark). It would be helpful to include more hands on excercise
创建者 Daxkumar J•
This course gives you a basic idea behind the pyspark. If you are a beginner so this course for you.
创建者 JOSE J M C•
Instructor pronunciation is not the best for someone who are not usually listening explain so fast.
创建者 Jochen G•
Cool course with a slow paced start and then interesting examples to work with Apache Spark ML.
创建者 Anaísa S•
Good course, but coach's English is poor and many corrections are made during presentations
创建者 126_YASH K•
Overall its an excellent course but I think more programing exercise should be there.