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Big Data Essentials

Big Data for Data Engineers,

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.

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Rating 3.4 based on 114 ratings
Length 7 weeks
Effort 6 weeks of study, 6-8 hours/week
Starts Jan 24 (89 weeks ago)
Cost $49
From Yandex via Coursera
Instructors Ivan Puzyrevskiy, Alexey A. Dral, Emeli Dral, Evgeniy Ryabenko, Evgeniy Riabenko, Pavel Mezentsev
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Software Development

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What people are saying

lot of time

I still do not understand map-side and reduce-side joins, and I do not feel comfortable writing a MapReduce job without a lot of time.The lectures over Hadoop were ok, but strange.

Assignments are not difficult but it takes a lot of time and attempts to figure out what exactly the authors wanted.

Task is easy, but takes a lot of time for debbuging on hdfs and understending whats wrong with submission.

This will save a lot of time!

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grading system

This week was pretty good and insightful around Map Reduce good course but grading system has some trouble This course very nice and cool, sometimes I want just stop it =) The course fills an important gap between software engineering and data engineering.

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.

The only thing that could be better is the grading system I am very glad that I completed this course, everything is extremely affordable.

), not so good topics (for introductory course), paranoid grading system.

The subject is very interesting but the grading system is very problematic and difficult.

the authors abandunded this course, no maintenance for the grading system.

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hard to understand

There's just too many things that can go wrong that are hard to understand unless you're already a somewhat experienced programmer and comfortable with the CLI.

sometimes it is hard to understand what the lecturer is saying.

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big data

This course has potential to improve and to be a very good course, but serious problems with the assignments or the graders, and the lack of care in the assembly of some lessons and their corresponding quizzes make impossible to recommend it to anyone interested in a serious and high quality course on the topics of big data.

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。 good course, covering a lot of foundations for Big Data and for Hadoop/Spark.

I do feel like I spent much more time trying to figure out how to make my answers pass the autograder rather than learning how to structure my code to solve big data problems.

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

Really recommend it if you wanna get a dive into the world of big data / divide and conquer via Hadoop!

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for beginners

This is definitely not a course for beginners.

Very great course for beginner in mapreduce...In detail and working map reduce knowledge Too quick to follow EXCELLENT This course is for beginners which have a couple of years of BigData experience Great Content if you are a beginner.

Too advanced for beginners.

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grader system

The nice and helpful course as usual because it was made by Yandex and BDTeam The course content is good, but you will have a horrible time with the grader system.

The assignments are straightforward, however you may face issues in the docker and in the grader system.

Very Good This course system had lots of bugs in grader system as well in the practice environment.

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more time

The assignments are described minimalistically, passing the automatic checking of the assignments cost more time than actually getting the right answer for the assignment and often the external assignment environment is down or not functioning correctly.

So far, I have spent more time dealing with these troubleshooting issues than actually focusing on the content.

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figure out

Submissions had lot of issues.I could not figure out and left the course in the middle(even the demo assignment was not working).The instructors were great but somehow I thought they were not very involved.Too much information (stated fast) out of which you may not be caring a lot.

understand what

I found that I had to listen to each lecture twice, once to get a general sense of where the lecture was going, and then a second time to actually understand what was being discussed.

I am unable to understand what the tutors have been talking.

very interesting

The contend is very interesting.

Other than that, the material of the course is very interesting.

feel comfortable

After this course, I do feel comfortable getting around in an HDFS, and I feel I have a basic understanding of how it works.The best part of the course was the lectures about Spark.

I feel comfortable using basic SPARK operations to manipulate data.If you wish to take this course, I recommend that you are knowledgeable about Linux Bash commands.

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Dept Chair & Teacher $40k

Instructor, Dept. of English $54k

Senior Teacher/Dept. Chair $66k

Marketing Dept. $70k

Emergency Dept Liaison $70k

Instructor, Music Dept. $71k

Colorado Internet Media Sales for Apt and Rentals $72k

Extrusion Dept Leader $74k

Assistant SAFETY & TRAINING DEPT $75k

Dept. of Anesthesia $77k

Quality Dept. $87k

Senior APT Analyst $142k

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Rating 3.4 based on 114 ratings
Length 7 weeks
Effort 6 weeks of study, 6-8 hours/week
Starts Jan 24 (89 weeks ago)
Cost $49
From Yandex via Coursera
Instructors Ivan Puzyrevskiy, Alexey A. Dral, Emeli Dral, Evgeniy Ryabenko, Evgeniy Riabenko, Pavel Mezentsev
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Software Development

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