About this Course
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Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 45 hours to complete

Suggested: 6 weeks of study, 6-8 hours/week...


Subtitles: English

Skills you will gain

Python ProgrammingApache HadoopMapreduceApache Spark

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 45 hours to complete

Suggested: 6 weeks of study, 6-8 hours/week...


Subtitles: English

Learners taking this Course are

  • Data Engineers
  • Data Scientists
  • Machine Learning Engineers
  • Data Analysts
  • Technical Solutions Engineers

Syllabus - What you will learn from this course

24 minutes to complete


8 videos (Total 14 min), 1 reading
8 videos
Issues BigData can solve1m
BigData Applications1m
What is BigData Essentials?2m
Course Structure2m
Meet Emeli1m
Meet Alexey2m
Meet Ivan1m
1 reading
Slack Channel is the quickest way to get answers to your questions10m
8 hours to complete

What are BigData and distributed file systems (e.g. HDFS)?

18 videos (Total 136 min), 10 readings, 4 quizzes
18 videos
File system managing6m
File content exploration 15m
File content exploration 213m
Scaling Distributed File System9m
Block and Replica States, Recovery Process 16m
Block and Replica States, Recovery Process 27m
HDFS Client9m
Namenode Architecture8m
Text formats9m
Binary formats 18m
Binary formats 28m
How to submit your first assignment3m
How to Install Docker on Windows 7, 8, 104m
10 readings
Basic Bash Commands10m
HDFS Lesson Introduction10m
Gentle Introduction into "curl"10m
File formats extra (optional)10m
Grading System: Instructions and Common Problems10m
Docker Installation Guide10m
HDFS CLI Playground30m
Programming Assignment: Instructions and Common Problems10m
FAQ How to show your code to teaching staff10m
Slack channel "Bigdata-coursera" - the quickest to solve technical problems.10m
2 practice exercises
Distributed File Systems16m
Big Data and Distributed File Systems25m
3 hours to complete

Solving Problems with MapReduce

17 videos (Total 94 min), 1 reading, 3 quizzes
17 videos
Unreliable Components 28m
Distributed Shell8m
Fault Tolerance7m
Fault Tolerance. Live Demo3m
Streaming in Python3m
WordCount in Python5m
Distributed Cache4m
Environment, Counters4m
Speculative Execution / Backup Tasks3m
1 reading
Hadoop Streaming Assignments: Intro and Code Samples10m
3 practice exercises
Hadoop MapReduce Intro26m
MapReduce Streaming26m
Hadoop Streaming Final30m
4 hours to complete

Solving Problems with MapReduce (practice week)

1 video (Total 3 min), 5 readings, 5 quizzes
5 readings
Hadoop Streaming Assignments: Intro and Code Samples10m
Hints to Debug Hadoop Streaming Applications10m
Grading System and Grading System Sandbox User Guide10m
Hadoop Streaming Assignments: Instructions10m
Hint to the "Stop words" programming assignment10m
3 hours to complete

Introduction to Apache Spark

16 videos (Total 95 min), 2 readings, 2 quizzes
16 videos
Transformations 16m
Transformations 27m
Execution & Scheduling6m
Caching & Persistence5m
Broadcast variables5m
Accumulator variables5m
Getting started with Spark & Python6m
Working with text files6m
Broadcast & Accumulator variables5m
Spark UI4m
Cluster mode3m
2 readings
Spark Assignments Intro10m
Instructions for Spark programming assignment10m
2 practice exercises
Lesson 1 Quiz20m
Lesson 2 Quiz24m
104 ReviewsChevron Right


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Top reviews from Big Data Essentials: HDFS, MapReduce and Spark RDD

By YHNov 22nd 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.

By SHMay 10th 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.



Ivan Puzyrevskiy

Technical Team Lead

Alexey A. Dral

Founder and Chief Executive Officer
BigData Team

About Yandex

Yandex is a technology company that builds intelligent products and services powered by machine learning. Our goal is to help consumers and businesses better navigate the online and offline world....

About the Big Data for Data Engineers Specialization

This specialization is made for people working with data (either small or big). If you are a Data Analyst, Data Scientist, Data Engineer or Data Architect (or you want to become one) — don’t miss the opportunity to expand your knowledge and skills in the field of data engineering and data analysis on the large scale. In four concise courses you will learn the basics of Hadoop, MapReduce, Spark, methods of offline data processing for warehousing, real-time data processing and large-scale machine learning. And Capstone project for you to build and deploy your own Big Data Service (make your portfolio even more competitive). Over the course of the specialization, you will complete progressively harder programming assignments (mostly in Python). Make sure, you have some experience in it. This course will master your skills in designing solutions for common Big Data tasks: - creating batch and real-time data processing pipelines, - doing machine learning at scale, - deploying machine learning models into a production environment — and much more! Join some of best hands-on big data professionals, who know, their job inside-out, to learn the basics, as well as some tricks of the trade, from them. Special thanks to Prof. Mikhail Roytberg (APT dept., MIPT), Oleg Sukhoroslov (PhD, Senior Researcher, IITP RAS), Oleg Ivchenko (APT dept., MIPT), Pavel Akhtyamov (APT dept., MIPT), Vladimir Kuznetsov, Asya Roitberg, Eugene Baulin, Marina Sudarikova....
Big Data for Data Engineers

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.