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返回到 Big Data Essentials: HDFS, MapReduce and Spark RDD

學生對 Yandex 提供的 Big Data Essentials: HDFS, MapReduce and Spark RDD 的評價和反饋

4.0
405 個評分
110 個審閱

課程概述

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....

熱門審閱

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.

篩選依據:

51 - Big Data Essentials: HDFS, MapReduce and Spark RDD 的 75 個評論(共 107 個)

創建者 Anshika M

Jun 19, 2019

EXCELLENT

創建者 Aldrin

Jul 11, 2019

Very great course for beginner in mapreduce...In detail and working map reduce knowledge

創建者 Aman A

Jul 31, 2019

Great Course.

創建者 shubham m

Aug 20, 2019

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

創建者 Minh T

Aug 24, 2019

Great

創建者 David B

Aug 27, 2019

Very good course with quite some tips, useful for real life scenarios. Some specific topics where not even covered in books nor on the internet to the depth covered in this course. Besides the knowledge, the authors put some hidden jokes here and there which gives you some laughs now and then. Really recommend it if you wanna get a dive into the world of big data / divide and conquer via Hadoop!

創建者 Alok K

Sep 16, 2019

Very Good

創建者 Amit V S

Sep 29, 2019

A well structured, to the point description, well designed exercises taught by brilliant instructors.

創建者 Marwen B A

Nov 04, 2019

great

創建者 EDWIN G C L

Dec 03, 2019

This course offers an understandable way to start working on Big Data! Highly recommended

創建者 Marco G

Dec 05, 2018

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.

創建者 Павел С

Dec 11, 2018

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!

創建者 Anand S

Jan 03, 2019

Great Course

創建者 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

創建者 Terry A

Mar 01, 2019

Good general overview, start to the subject. Frustrated at consistent issues with development environment and/or ability to debug. Responses to questions and mentor assistance is seriously lacking.

創建者 DIEGO A R

Aug 02, 2018

Excelente curso, falta más realmentación por parte de los profesores, pero en general aunque el contenido es Denso y se requieren más horas de lo estipulado en el curso, es muy bueno.

創建者 Bo T

Sep 06, 2018

The assignment cannot submit correctly. Really disappointed!

創建者 Gregory R

Apr 27, 2018

Great course! Please, follow up with discussion boards more. Otherwise, happy I took it.

Also, looking forward to the entire specialization ready, like course #4 about real Time Streaming.

創建者 Martin T

Feb 05, 2018

Lectures are very good and I learned a lot.

創建者 Vladimir

Dec 02, 2017

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

創建者 yunwoo n

May 17, 2018

good course but grading system has some trouble

創建者 Lyashko K

Jan 31, 2018

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

創建者 Alexander K

Mar 05, 2018

Requires intermediate skills and ability to work on your own.

創建者 Simon V L

Jan 31, 2018

The content of the course is really good. THe assignments should be made a lot clearer and the jupyter grading tool is full of bugs.

創建者 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.