Its very useful course, good trainers are explained very detail.

This course very nice and cool, sometimes I want just stop it =)

This week was pretty good and insightful around Map Reduce

Awesome course, goes very deep into the details.

Excellent course content covering in depth.

This is really Intermediate level course.

Awesome content...great learning ...:)

Great Content if you are a beginner.

Very Nice..............Intraction

<Good learning >

good knowledge

Great Course.

Excellent!

Very Good

EXCELLENT

great

Great

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The course undoubtedly provides high value and does a good job of introduction of a learner to the basics of big data technologies. I would highly recommend to do the Honors tasks along with the required assignments. There is still a room for improvement, though. The English level does not obstruct the understanding of the material but could be better. Also accurate subtitles, better graphic material, clearer task requirements and more stable grader system would be welcome. The last point might not be a problem anymore, as the grader system seem to have been overhauled in the last few weeks and have been working fine for me since. The slack support channel is active. Kudos to the teachers.

The course is very useful and gives you the basics you need about HDFS, Map-Reduce in python (there is no java in this course) and pyspark. The assignments are straightforward, however you may face issues in the docker and in the grader system. The cons of this course is that sometimes information is given in a fast pace which somehow can make you get confused and unable to fully digest the material. Also there is no interaction at all from the instructors, it'll be nice if they can keep up with students' questions and issues in the future!

Потратил больше времени на то, чтобы Grader правильно принял решения, чем времени на решение задачи. Потратить 3-4 часа на решение исходной задачи и потратить 10 часов (включая форум и Slack) на то чтобы ответ правильно принять. Особенно на задаче с Твиттер датасетом, ругается на количество редусеров, но оказывается, надо было логи yarn тоже выводить.

Хорошо было бы добавить еще одну проверку, которая проверяет выводятся ли логи yarn и сообщать, что его нет.

Если бы не эта проблема, поставил бы 5 звезд.

I think students could choose MapReduce or Spark. And about shortest path task. Provided by authors code runs out of memory while checking on cluster. After a lot of time playing with spark paramets and cache/persist i found solution without calculating all distances, but... Also there was no information about spark executors parameters on course...

Simple hint could save a lot of stupidly wasted time.

But it's not major, anyway thanks!

Practice work in this course is divided in two part. First, you try to solve an assignment into your home Docker environment. It's really interesting to do it in spite of the assignments is not very clear. Second, you try to put the result into the course's grader system. For me, Grader it's like a Major Payne. You will get an amazing experience to work with production cluster through not well suited environment.

Interesting, useful, informative, accessible (and sometimes funny!) lectures.

Stimulating assignments.

Fast responses from instructors/mentors.

Unfortunately, I often spent more time trying to get my assignments to pass the automatic grader than on solving them. This made the course a bit frustrating at times.