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Big Data Essentials: HDFS, MapReduce and Spark RDD に戻る

Yandex による Big Data Essentials: HDFS, MapReduce and Spark RDD の受講者のレビューおよびフィードバック

4.0
421件の評価
115件のレビュー

コースについて

Have you ever heard about such technologies as HDFS, MapReduce, Spark? Always wanted to learn these new tools but missed concise starting material? Don’t miss this course either! In this 6-week course you will: - learn some basic technologies of the modern Big Data landscape, namely: HDFS, MapReduce and Spark; - be guided both through systems internals and their applications; - learn about distributed file systems, why they exist and what function they serve; - grasp the MapReduce framework, a workhorse for many modern Big Data applications; - apply the framework to process texts and solve sample business cases; - learn about Spark, the next-generation computational framework; - build a strong understanding of Spark basic concepts; - develop skills to apply these tools to creating solutions in finance, social networks, telecommunications and many other fields. Your learning experience will be as close to real life as possible with the chance to evaluate your practical assignments on a real cluster. No mocking, a friendly considerate atmosphere to make the process of your learning smooth and enjoyable. Get ready to work with real datasets alongside with real masters! Special thanks to: - Prof. Mikhail Roytberg, APT dept., MIPT, who was the initial reviewer of the project, the supervisor and mentor of half of the BigData team. He was the one, who helped to get this show on the road. - Oleg Sukhoroslov (PhD, Senior Researcher at IITP RAS), who has been teaching MapReduce, Hadoop and friends since 2008. Now he is leading the infrastructure team. - Oleg Ivchenko (PhD student APT dept., MIPT), Pavel Akhtyamov (MSc. student at APT dept., MIPT) and Vladimir Kuznetsov (Assistant at P.G. Demidov Yaroslavl State University), superbrains who have developed and now maintain the infrastructure used for practical assignments in this course. - Asya Roitberg, Eugene Baulin, Marina Sudarikova. These people never sleep to babysit this course day and night, to make your learning experience productive, smooth and exciting....

人気のレビュー

YH

Nov 22, 2018

Everything in this course is new to me, but it provides me with many practice so I can gradually get familiar with all these new stuff. I find it a bit challenging, but overall it's quite good.

SH

May 10, 2019

The course takes you from basic level , step level .But It is quite fast for beginners , you may need pause video in between and try to understand the concept.

フィルター:

Big Data Essentials: HDFS, MapReduce and Spark RDD: 76 - 100 / 112 レビュー

by Casper Y

Feb 18, 2018

The practises are practical and useful. However, there is an initial learning curve to get use to the grading tools.

by David A Z T

Feb 17, 2019

The content was a nice introductory course. The only thing that could be better is the grading system

by Vladimir

Dec 02, 2017

Good course, but the description of practical tasks is not always clear.

by Lyashko K

Jan 31, 2018

Only four because of graduating tool. The contend is very interesting.

by Shreeharsha G

Jun 27, 2018

Challenging !! But need some more help on slack and active community.

by Rain

May 24, 2019

其实课程内容设计还是挺不错的,配合资料对Mapreduce和hdfs基本设计思路都有很好的了解,但是课程的编程l练习不置可否。

by Alexander K

Mar 05, 2018

Requires intermediate skills and ability to work on your own.

by Bo T

Sep 06, 2018

The assignment cannot submit correctly. Really disappointed!

by SAI V K

Oct 29, 2019

Course is good,but the grader doesnt work properly.

by yunwoo n

May 17, 2018

good course but grading system has some trouble

by Martin T

Feb 05, 2018

Lectures are very good and I learned a lot.

by saranbabu

Nov 30, 2019

nice experience

by Anand S

Jan 03, 2019

Great Course

by Rumen K

Jan 22, 2020

good

by Janneke V

Feb 01, 2018

Learned a lot, but the videos alone aren't really enough to get you through the assignments. Also, the assignments have a 'bottleneck' at the grading system where you know the answer is correct yet the grader won't accept it because your route to the answer is different than standard.

by Nagarajan

May 14, 2019

The course content is good, but you will have a horrible time with the grader system. You will have to spend lot of additional hours which you shouldn't be. I could have learned a lot more if the assignments are clear and if the mentors are active. Many links are broken as well.

by Guryanov A

Jun 14, 2018

Practical tasks could use some work: it would not hurt to have more of them, but to improve them with good notebooks like Andrew NG's deep learning course (maybe not as simple as his, but mode informative for sure)

by Dmitry P

Oct 19, 2018

Quizzes in this course ask questions that are not covered in lectures. Subtitles are full of mistakes and typos. Other than that, the material of the course is very interesting.

by Alexey S

Jan 29, 2018

Good (not excellent) as a technical presentations, but mediocre as a university class .

Clearly. done by an engineer, not a professional teacher

by Usman

Feb 27, 2018

Great course but the assignments are a mess. The grader is unreliable and they are all sorts of problems. The content is great though.

by Alberto B

Jun 26, 2018

Bad support, terrible problems with the UI, some homeworks are poorly explained. Nevertheless, the course's content is very good.

by Aleksey A

Dec 03, 2017

Good material, but very slow system for check hadoop and spark notebooks. I spent much more hours for complete practice tasks.

by Nedashkovsky S

Nov 18, 2019

It's interesting course, but the loss of time due to incorrect operation of the task verification system is frustrating

by Harish S

Oct 26, 2018

Too advanced for beginners. Some working knowledge needed in big-data stream before starting this course.

by Arnab B

Dec 26, 2019

The lectures are very fast and to me accent for some of the presenters are difficult to understand.