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Retour à Big Data Essentials: HDFS, MapReduce and Spark RDD

Avis et commentaires pour d'étudiants pour Big Data Essentials: HDFS, MapReduce and Spark RDD par Yandex

4.0
étoiles
507 évaluations
135 avis

À propos du cours

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....

Meilleurs avis

YH
21 nov. 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
9 mai 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.

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76 - 100 sur 132 Avis pour Big Data Essentials: HDFS, MapReduce and Spark RDD

par Oliver P

31 mars 2020

Overall, a sound introduction of the topic. The first time, I understood these technologies. From time to time the tutorials and introduction videos have been a bit too quick, too sketchy to understand the content properly.

par Terry A

28 févr. 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.

par Waldemar D

19 mai 2019

good course, covering a lot of foundations for Big Data and for Hadoop/Spark. Also one of the few that focus on Data Engineering perspective rather than Data Science. Learned a lot here!

par Gregory R

27 avr. 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.

par DIEGO A R

1 août 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.

par Alois T

5 nov. 2020

The course is pretty ok, but beware to bend under the constraints of the automatic corrector. You can spend many hours just "fixing" your code despite having the good result

par Taras P

12 mai 2018

Materials are good, but there was a lot of problem with assignment clear understanding and infrastructure. Also would like to pass this course on Scala.

par Mahendra A

16 mars 2020

Overall course was good and informative.. Sometime it feels lil bit tough to grasp may be due to as its an entirely different domain for me

par Tomiwa k

8 nov. 2019

the curriculum is fine, I learnt new things. the authors abandunded this course, no maintenance for the grading system. this shows be fixed

par Simon V L

31 janv. 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.

par Casper Y

18 févr. 2018

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

par Abijith K

29 févr. 2020

Expected more depth in Spark architecture but was kept at a high level

Course on HDFS were really good

par David Z

17 févr. 2019

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

par Vladimir

2 déc. 2017

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

par Lyashko K

31 janv. 2018

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

par Shreeharsha G

27 juin 2018

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

par Rain

23 mai 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。

par Alexander K

5 mars 2018

Requires intermediate skills and ability to work on your own.

par Bo T

6 sept. 2018

The assignment cannot submit correctly. Really disappointed!

par SAI V K

29 oct. 2019

Course is good,but the grader doesnt work properly.

par yunwoo n

16 mai 2018

good course but grading system has some trouble

par Martin T

5 févr. 2018

Lectures are very good and I learned a lot.

par Antonina B

16 sept. 2020

Really great course, but needs an update!

par Yasiru J R

3 juin 2020

Some explanations of concepts not clear

par saranbabu

30 nov. 2019

nice experience