About this Course
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Advanced Level

Approx. 74 hours to complete

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


Subtitles: English, Korean

Skills you will gain

GraphsHiveApache HiveApache Spark

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 74 hours to complete

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


Subtitles: English, Korean

Syllabus - What you will learn from this course

22 minutes to complete

Welcome to the Second Course: Big Data Analysis

8 videos (Total 12 min), 1 reading
8 videos
What is BigData Analysis?1m
Tools For BigData Analysis1m
Graph Data Analysis2m
Meet Alexey Dral2m
Meet Pavel Mezentsev37s
Meet Natalia Pritykovskaya40s
Meet Pavel Klemenkov40s
1 reading
Slack Channel is the quickest way to get answers to your questions10m
3 hours to complete

Big Data SQL: Hive

15 videos (Total 105 min), 3 quizzes
15 videos
HTTP Web Service: Access Log Format4m
Business Use Cases: Solution with Hive6m
(optional) SQL: likbez10m
Hive Data Definition Language (DDL)11m
Hive Data Manipulation Language (DML)6m
Hive Analytics: RegexSerDe, Views7m
(optional) Regular Expressions, Likbez9m
Hive Analytics: UDF, UDAF, UDTF7m
Hive Streaming4m
Hive PTF (Window Functions)5m
Hive Optimization: Partitioning, Bucketing and Sampling8m
Hive Map-Side Joins: Plain, Bucket, Sort-Merge5m
Hive Optimization: Data Skew4m
Hive Optimization: Row-Columnar File Formats, Compression8m
3 practice exercises
Hive: SQL over Hadoop MapReduce20m
Hive Analytics with UDF and Streaming20m
Hive final20m
7 hours to complete

Big Data SQL: Hive (practice week)

3 videos (Total 11 min), 6 readings, 5 quizzes
3 videos
How to Install Docker on Windows 7, 8, 104m
How to submit your first Hadoop assignment3m
6 readings
Assignments. General requirements10m
Hive assignment. Intro and instructions10m
Grading System: Instructions and Common Problems10m
Docker Installation Guide10m
Copy of Assignments. General requirements10m
Copy of Assignments. General requirements10m
2 hours to complete

Spark SQL and Spark Dataframe

14 videos (Total 82 min), 2 quizzes
14 videos
What is Pandas DataFrame and how to create it4m
How to process a DataFrame as SQL4m
Working with Hive4m
Reading and Writing Files7m
RDD vs. DF vs. SQL3m
Projection and Filtering5m
User Defined Functions8m
Time Processing4m
Window Functions7m
Two-Dimensional Distributions4m
2 practice exercises
Introducing DataFrame and SQL16m
Spark SQL and Spark Dataframe18m
4 hours to complete

Graph Analysis from Big Data Perspective

13 videos (Total 83 min), 5 quizzes
13 videos
Graph representation7m
Counting common friends. Part I2m
Counting common friends. Part II10m
Counting common friends. Part III5m
GraphFrames: Introduction6m
Motif Finding: DSL6m
Motif Finding: Counting Mutual Friends6m
Motif Finding: Under The Hood. Part 114m
Motif Finding: Under The Hood. Part 24m
Triangles Count: Introduction3m
Triangles Count: Edge Lists6m
Triangles Count: GraphFrame6m
4 practice exercises
Graph Representations10m
Motif Finding18m
Triangles Count8m
Graph Analysis from Big Data Perspective20m
9 hours to complete

PageRank and Recent Advances

10 videos (Total 72 min), 1 reading, 10 quizzes
10 videos
Random Walk5m
Page Rank Algorithm10m
RDD Implementation4m
GraphFrames API4m
Taste Graph. Part I10m
Taste Graph. Part II3m
Taste Graph. Part III9m
1 reading
Graph based Music Recommender10m
4 practice exercises
Connected Components12m
Label Propagation Algorithm (LPA)10m
PageRank and Recent Advances18m
4 hours to complete

Spark Internals and Optimization

17 videos (Total 87 min), 1 reading, 5 quizzes
17 videos
Spark Execution Model5m
Shuffle. Where to send data?5m
Shuffle. How to send data?4m
Optimizing Functions4m
PageRank Optimization5m
Spark SQL. Motivation8m
Catalyst Optimization Example5m
Optimizing Joins5m
UDF Optimization5m
Persistance and Checkpointing7m
Memory Management3m
Resource Allocation6m
Dynamic Allocation5m
Speculative Execution4m
1 reading
Deployment of the environment10m
4 practice exercises
Spark Execution Model & RDD Internals10m
Spark SQL and Catalyst10m
Memory management and resource allocation10m
Final Quiz16m
21 ReviewsChevron Right


started a new career after completing these courses


got a tangible career benefit from this course

Top reviews from Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames

By SMNov 13th 2018

content of the course is remarkable and the way they explained concepts is very lucid. I just want to give suggestions please give link to the data set they are using for illustrating the concepts.

By SSFeb 3rd 2018

I wish I could give more rating than 5 :). Excellent course. Thanks so much for such an excellent course. All the instructors are great.



Pavel Klemenkov

Chief Data Scientist

Pavel Mezentsev

Senior Data Scientist
PulsePoint inc

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.