Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames by Yandex via Coursera: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course overview

We are witnessing a phenomenal era, which is digitally powered with technologies flourishing exponentially. With the strong presence of Big Data, computer systems are now capable of deriving acute information and desired results through analysis of this structured and unstructured data, which ultimately forms the ‘big data’. It is also witnessed that such analysis of Big Data is highly relevant and informative for large organisations, businesses and professionals to optimize their performances.

Considered to be information assets, Big Data enables effective decision making, optimizing processes and cost effectiveness in large, medium as well as small organisations. However, to yield the benefits of this high volume, high velocity and high variety of big data, it becomes essential to analyse this big data using various tools and techniques. This is where the knowledge of using Hive, Spark SQL, DataFrames and GraphFrames comes very handy. Analysts engaged in big data analysis are highly in demand and using these tools, one can efficiently analyse the big data to facilitate important decision making and process optimisation in their employer organisations.

The Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames online programme offered by Coursera will impart key skills to the participants in using big data analysis tools and pursue their careers in the area of big data analysis.

Course and certificate fees

Type of course

Free

Coursera offers this course via Purchase Course and Audit-Only Options.
The price of purchasing the course is Rs. 2,159.
There are no charges for Audit Mode. However, participants will not be able to gain access to graded assignments required to earn the certificate.

Fee details for Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames Course

Course Purchase Fees	Rs. 2,159 (includes full access to course material and graded assignments)
Audit Only	Free access to course material except graded assignments
Financial Aid	Available on application

certificate availability

Yes

certificate providing authority

Coursera

certificate fees

₹2,152

Who it is for

Big data developer It engineer Big data analytics engineer Big data engineer

Eligibility criteria

Certification Qualifying Details

In order to avail the certificate of completion, participants of The Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames certificate course will have to complete as well as pass in all the graded items attached to the course. These assignments will consist of quizzes and other assignments (if applicable). Upon passing in these assignments, Coursera will issue an electronic certificate of completion which will be automatically added to the accomplishment page of participants. further, this certificate can be shared online via URL as well as be printed.

What you will learn

Knowledge of apache spark

Upon completion of The Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames, participants of the Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames course will be able to:

Process graphs using the Spark GraphFrames
Construct and use Spark DataFrames
Write ad-hoc analytical jobs using Spark DataFrames
Optimize and debug Spark application performance to its maximum
Use Hive, Spark DataFrames and Spark SQL to efficiently warehouse your data
Make effective use of networks and social graphs
Write and executive queries using Hive and Spark SQL

The syllabus

Welcome to the Second Course: Big Data Analysis

Videos

Meet Alexey Dral
Meet Natalia Pritykovskaya
Meet Pavel Klemenkov
Meet Pavel Mezentsev
What is BigData Analysis?
Tools for BigData Analysis
Graph Data Analysis
Computations Optimization

Readings

Slack Channel is the quickest way to get answers to your questions

Big Data SQL: Hive

Videos

Hive Data Definition Language (DDL)
Hive Data Manipulation Language (DML)
Hive Analytics: RegexSerDe, Views
Hive Streaming
Hive Optimization: Data Skew
Analytics: Business Use Cases
Business Use Cases: Solution with Hive
HTTP Web Service: Access Log Format
Hive Analytics: UDF, UDAF, UDTF
Hive Optimization: Partitioning, Bucketing and Sampling
Hive PTF (Window Functions)
Hive Map-Side Joins: Plain, Bucket, Sort-Merge
Hive Optimization: Row-Columnar File Formats, Compression
(optional) Regular Expressions, Likbez
(optional) SQL: likbez

Big Data SQL: Hive (practice week)

Videos

How to Install Docker on Windows 7, 8, 10
How to submit your first Hive assignment
How to submit your first assignment

Readings

Docker Installation Guide
Hive assignment. Intro and instructions
Assignments. General requirements
Grading System: Instructions and Common Problems

Spark SQL and Spark Dataframe

Videos

How to process a DataFrame as SQL
Advantages of Spark SQL
Working with Hive
What is Pandas DataFrame and how to create it
RDD vs. DF vs. SQL
Aggregates
User Defined Functions
Functions
Projection and Filtering
Reading and Writing Files
Time Processing
Window Functions
Two-Dimensional Distributions
Join

Graph Analysis from Big Data Perspective

Videos

Counting common friends. Part I
Graph representation
Counting common friends. Part II
Graph examples
GraphFrames: Introduction
Motif Finding: DSL
Counting common friends. Part III
Motif Finding: Counting Mutual Friends
Triangles Count: Introduction
Motif Finding: Under The Hood. Part 1
Triangles Count: Edge Lists
Triangles Count: GraphFrame
Motif Finding: Under The Hood. Part 2

PageRank and Recent Advances

Videos

Introduction
GraphFrames
Algorithm
Taste Graph. Part I
Page Rank Algorithm
GraphFrames API
Taste Graph. Part II
RDD Implementation
Taste Graph. Part III
Random Walk

Readings

Graph based Music Recommender

Spark Internals and Optimization

Videos

Welcome
Shuffle. Where to send data?
Shuffle. How to send data?
Spark Execution Model
PageRank Optimization
Optimizing Functions
Catalyst
Spark SQL. Motivation
UDF Optimization
Joins
Optimizing Joins
Catalyst Optimization Example
Resource Allocation
Memory Management
Speculative Execution
Persistence and Checkpointing
Dynamic Allocation

Readings

Deployment of the environment

Admission details

To enrol for the Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames online certificate course, the participants are required to follow the below mentioned steps.

Step 1: Visit the course page.

Step 2: Click on the “Enroll for Free” box.

Step 3: Log in or sign up using your Google or Email credentials.

Step 4: You will have the option of “Purchase Course” and “Audit Only”. “Purchase Course” will enable the applicants to receive full access to all course material and graded assignments. Through the “Audit Only” option, applicants will only receive access to course content, and not the graded items.

Step 5: Choose the option of your choice and proceed to make payment.

Please note that applicants via the “Audit Only” option, applicants will be able to access the course content, but not the graded assignments, which is required to avail course completion certificate from Coursera.

Scholarship Details

Coursera offers financial aid/sponsorship support for this course. Through this, participants will be able to access the entire course content including the graded assignments in order to earn the course completion certificate.

To apply for financial aid/scholarship, follow these steps.

Step 1: Click on the ‘Financial aid available’ button on the course homepage. Enter your desired log-in credentials to proceed.

Step 2: Fill the application form with basic information and required fields. To avoid rejection, ensure that the application is more than 150 words.

Step 3: While your application is being reviewed, you can begin the course through audit mode. Please note that the review process can take up to 15 days.

Step 4: Upon review, Coursera will notify your application status as accepted or rejected/denied via email. In the case of application being accepted, participants will be directly enrolled in the course.

Step 5: Participants will have 2 weeks’ time to unenroll from the course, once the application has been accepted.

Evaluation process

Participants will be required to pass in all the graded assignments of the course to earn the course completion certificate from Coursera. These assignments will consist majorly of quizzes and any other applicable assignments given by the instructors. Participants can opt for flexible deadlines, as well as save their progress to be picked up later. Participants will be eligible for a shareable Certificate from Coursera only after completing and passing all the required graded assignments.

How it helps

In this highly digitised era, technological advancements are beaming and achieving new heights. Digitalisation is simplifying processes and optimizing performance, allowing the businesses to flourish more efficiently. This is possible because of useful, informative and critical analysis of ‘Big Data’. Participants of this online course will be benefited with knowledge and skills to use various tools for building highly dynamic and well-organised big data workflows.

Through this online certification course, participants will gain useful insights and working knowledge of Hive, Spark SQL, DataFrames and GraphFrames, which will enable them to efficiently warehouse their data, write and execute queries, as well as work with social graphs and networks. The participants will benefit a great deal by gaining knowledge of Pandas DataFrame, Aggregates, PageRank Optimization, Memory Management and various other tools of big data analysis. The participants will also receive a shareable certificate from Coursera upon completion of the course.

Globally, there is a surge in demand for big data analysts and business analysts who possess the competency to deal with a humongous volume of data. By attending and completing this course, the participants will receive exposure to tools and techniques used in analysing big data and strengthen their skills and competencies to assist their employer organisations in better decision making, forecasting, cost reduction and process optimisation. Participants will also receive their training tutorials from leading instructors representing the big data analysis field.

FAQs

Is there a prerequisite to enrol for The Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames course?

This course is an advanced level course designed to deliver learning on making use of big data analysis tools like Hive, Spark SQL, DataFrames and GraphFrames, irrespective of the personal skill levels of the participants.

How does the Audit Only option work?

Through the Audit Only option, participants will be able to access only the course material consisting of videos and readings, and not the graded assignments like quizzes. Participants do not have to pay any fees or charges to ‘audit’ the course.

Who can become eligible for certification in The Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames?

Only those participants who have completed all the course work and have passed with sufficient grades will become eligible for Coursera certification.

How does the shareable course certificate work?

You will receive your certificate once you have passed in all the graded assignments. From the accomplishments page, you can share the certificate online on LinkedIn, CV and more, as well as print the same.

What is the Purchase Course method?

By purchasing the course, participants will have access to full contents of the course including quizzes and other graded assignments required to earn certification.