Certified Big Data and Hadoop Training Course

Big Data and Hadoop course from DataFlair is a great blend of in-depth theoretical knowledge and strong practical skills via implementation of real life projects to enable you head start and grab top Big Data jobs in the industry.

40+ Hrs of instructor-led sessions
100+ Hrs of practicals & assignments
5 Real-time big data projects
Lifetime access to course with support
Job oriented course with job assistance

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Offers: Get Apache Storm & Java courses free with instructor-led Course

About Big Data Hadoop Course

Big Data Hadoop online training course is designed by certified experts as per industry standards and need to make you quite apt to grab top jobs and start your career as Big Data developer as thousands of other professionals have already done by joining this Hadoop course.

Become Hadoop Big Data expert by learning core Big Data technology and gain hands on knowledge of Hadoop along with its eco-system components like HDFS, Map-Reduce, Hive, Pig, HBase, Sqoop, Flume, Yarn and Apache Spark through this Hadoop course. For extensive hands-on, individual topics are explained using multiple workshops. The online Big data and Hadoop certification course also covers real life use-cases, multiple POCs, live Hadoop project and create foundation of Apache Spark for distributed data processing.

Objectives of Big Data Hadoop online Training

Bring shift in your career as Big data has brought in IT world
Grasp the concepts of HDFS and Map Reduce
Become adept in latest version of Apache Hadoop
Develop complex Game-Changing MapReduce Application
Data analysis using Pig and Hive
Play with NoSQL database – Apache HBase
Acquire understanding of ZooKeeper service
Data loading using Apache Sqoop and Flume
Enforce best practices for Hadoop development and deployment
Master handling of large data-set using Hadoop ecosystem
Work on live project on Big Data analytics to get hands-on Experience
Comprehend other Big Data technologies like Apache Spark

Upcoming Batch Schedule

START-DATE	TIME	DAYS	DURATION
17 Dec – 11 Jan	09.00 PM – 11.00 PM IST 7.30 AM – 09.30 AM PST	Mon-Fri	40 Hrs
22 Dec – 27 Jan	8.00 PM – 11.00 PM IST 09.30 AM – 12.30 PM EST	Sat-Sun	40 Hrs
14 Jan – 8 Feb	09.00 PM – 11.00 PM IST 7.30 AM – 09.30 AM PST	Mon-Fri	40 Hrs
12 Jan – 17 Feb	10.00 AM – 01.00 PM IST 08.30 PM – 11.30 PM PST	Sat-Sun	40 Hrs
9 Feb – 17 Mar	8.00 PM – 11.00 PM IST 09.30 AM – 12.30 PM EST	Sat-Sun	40 Hrs

Who should go for this online Hadoop Course

YOU, yes you should go for this Big Data and Hadoop online course if you want to take a leap in your career as Hadoop developer. This course will be useful for:

Software developers, Project Managers and architects
BI, ETL and Data Warehousing Professionals
Mainframe and testing Professionals
Business analysts and Analytics professionals
DBAs and DB professionals
Professionals willing to learn Data Science techniques
Any graduate focusing to build career in Big Data

Pre-requisites to attend Hadoop online course

Nothing can stop you from starting your career in Big Data. As such no prior knowledge of any technology is required to learn Big Data and Hadoop. In case you feel any need to revise your Java concepts, Java course will be provided in your LMS as complimentary with our Big Data and Hadoop tutorial course.

Highly experienced instructors

1 to 1 interaction with the instructor

5 Real time Big Data projects

100% Job assistance and support

Lifetime access to the course

1.Big Picture of Big Data

What is Big Data
Necessity of Big Data in the industry
Paradigm Shift - why industry is shifting to Big Data tools
Different dimensions of Big Data
Data explosion in industry
Various implementations of Big Data
Different technologies to handle Big Data
Traditional systems and associated problems
Future of Big Data in IT industry

2.Demystify what is Hadoop

Why Hadoop is at the heart of every Big Data solution
Introduction to Hadoop framework
Hadoop architecture and design principles
Ingredients of Hadoop
Hadoop characteristics and data-flow
Components of Hadoop ecosystem
Hadoop Flavors – Apache, Cloudera, Hortonworks etc.

3.Setup and Installation of Hadoop

Setup and Installation of Single-Node Hadoop Cluster

Setup of Hadoop environment and pre-requisites
Installation and configuration of Hadoop
Work with Hadoop in pseudo-distributed mode
Troubleshooting the encountered problems

Setup and Installation of Hadoop multi-node Cluster

Setup Hadoop environment on the cloud (Amazon cloud)
Install Hadoop pre-requisites on all the nodes
Configuration of Masters and Slaves on Cluster
Play with Hadoop in distributed mode

4.HDFS – Storage Layer

What is HDFS - Hadoop Distributed File System
HDFS daemons and its Architecture
HDFS data flow and its storage mechanism
Hadoop HDFS Characteristics and design principles
Responsibility of HDFS Master – NameNode
Storage mechanism of Hadoop meta-data
Work of HDFS Slaves – DataNodes
Data Blocks and distributed storage
Replication of blocks, reliability and high availability
Rack-awareness, Scalability and other features
Different HDFS APIs and terminologies
Commissioning of nodes and addition of more nodes
Expand the cluster in real-time
Hadoop HDFS web UI and HDFS explorer
HDFS Best Practices and hardware discussion

5.Deep Dive into MapReduce

What is MapReduce - Processing layer of Hadoop
Need of distributed processing framework
Issues before MapReduce and its evolution
List processing Concepts
Components of MapReduce – Mapper and Reducer
MapReduce terminologies key, values, lists etc.
Hadoop MapReduce execution flow
Mapping data and reducing them based on keys
MapReduce word-count example to understand the flow
Execution of Map and Reduce together
Control the flow of mappers and reducers
Optimization of MapReduce Jobs
Fault-tolerance and data locality
Work with map-only jobs
Introduction to Combiners in MapReduce
How MR jobs can be optimized using Combiners

6.MapReduce - Advanced Concepts

Anatomy of MapReduce
Hadoop MapReduce data-types
Develop custom data-types using Writable & WritableComparable
What is InputFormats in MapReduce
How InputSplit is unit of work
How Partitioners partition the data
Customization of RecordReader
Move data from mapper to reducer – shuffling & sorting
Distributed Cache and job chaining
Different Hadoop case-studies to customize each component
Job scheduling in MapReduce

7.Hive – Data Analysis Tool

Need of adhoc SQL based solution – Apache Hive
Introduction and architecture of Hadoop Hive
Play with Hive shell and run HQL queries
Hive DDL and DML operations
Hive execution flow
Schema Design and other Hive operations
Schema on read vs Schema on write in Hive
Meta-store management and need of RDBMS
Limitation of default meta-store
Using serde to handle different types of data
Optimization of performance using partitioning
Different Hive applications and use cases

8.Pig – Data Analysis Tool

Need of high level query language - Apache Pig
How pig complements Hadoop with scripting language
What is Pig
Pig execution flow
Different Pig operations like filter and join
Compilation of pig code into MapReduce
Comparison between Pig vs MapReduce

9.NoSQL Database - HBase

NoSQL Databases and their need in the industry
Introduction to Apache HBase
Internals of HBase architecture
HBase master and slave model
Column-oriented, 3 dimensional, schema-less datastore
Data modeling in Hadoop HBase
Store multiple versions of data
Data high-availability and reliability
Comparison between HBase vs HDFS
Comparison between HBase vs RDBMS
Data access mechanism
Work with HBase using shell

10.Data Collection using Sqoop

Need of Apache Sqoop
Introduction and working of Sqoop
Import data from RDBMS to HDFS
Export data to RDBMS from HDFS
Conversion of data import / export query into MapReduce job

11.Data Collection using Flume

What is Apache Flume
Flume architecture and aggregation flow
Understand Flume components like data Source and Sink
Flume channels to buffer the events
Reliable & scalable data collection tool
Aggregate streams using Fan-in
Separate streams using Fan-out
Internals of agent architecture
Production architecture of Flume
Collect data from different sources to Hadoop HDFS
Multi-tier flume flow for collection of volumes of data using avro

12.Apache Yarn & Advanced concepts in latest version

Need and evolution of Yarn
What is Yarn and its eco-system
Yarn daemon architecture
Master of Yarn – Resource Manager
Slave of Yarn – Node Manager
Resource request from Application master
Dynamic slots called containers
Application execution flow
MapReduce version 2 application over Yarn
Hadoop Federation and Namenode HA

13. Processing Data with Apache Spark

Introduction to Apache Spark
Comparison between Hadoop MapReduce vs Apache Spark
Spark key Features
RDD and various RDD operations
RDD Abstraction, interface and creation of RDDs
Fault Tolerance in Spark
Spark Programming model
Data Flow in Spark
Spark Ecosystem, its Hadoop compatibility & integration
Installation & Configuration of Spark
Process Big Data using Spark

14.Real Life Project on Big Data

Features

Course mode

Extensive hands-on practicals

Access Duration

Real-life Project

No of Projects

Discussion Forum Access

Doubt Clearance

Certification

Complementary Courses

Complementary Job Assistance

Resume & Interview Preparation

Interaction in Live class

Personalized career guidance

Course Objective

Self-Paced Pro Course

Rs. 4990 | $90

Video Based

Yes, in recordings & in LMS

Lifetime

Yes

One

Lifetime

Through discussion forum

Yes, post course completion

Java, with lifetime access

Express Learning

Enroll Now!

Live Instructor-Led Course

Rs. 12990 | $236

Live Online with Trainer

Yes, live with instructor & in LMS

Lifetime

Yes, with support

Five

Lifetime

In regular sessions

Yes, post course completion

Java & Storm, with lifetime access

Yes

100% interactive classes

Yes, from instructor

Job readiness

Enroll Now!

How will you help me if I miss any Hadoop training session?

If you miss any session, you need not worry as recordings will be uploaded in LMS immediately as the session gets over. You can go through it and get your queries cleared from the instructor during next session. You can also ask him to explain the concepts that you did not understand and were covered in session you missed. Alternatively you can attend the missed session in any other batch running parallely.

How will I do Big Data Hadoop practicals at home?

Instructor will help you in setting virtual machine on your own system at which you can do practicals anytime from anywhere. Manual to set virtual machine will be available in your LMS in case you want to go through the steps again. Virtual machine can be set on MAC or Windows machine also.

How long will the Hadoop course recording available with me?

All the sessions will be recorded and you will have lifetime access to the recordings along with the complete Hadoop study material, POCs, Hadoop project etc.

What things do I need to attend Hadoop online classes?

To attend online Hadoop training, you just need a laptop or PC with a good internet connection of around 1 MBPS (But the lesser speed of 512 KBPS will also work). The broadband connection is recommended but you can connect through data card as well.

How can I get my doubts cleared post class gets over?

If you have any doubt during any session, you can get it cleared from the instructor immediately. If you get queries after the session, you can get it cleared from the instructor in the next session as before starting any session, instructor spends around 15 minutes in doubt clearing. Post training, you can post your query over discussion forum and our support team will assist you. Still if you are not comfortable, you can drop mail to instructor or directly interact with him.

What are the system specifications required to learn Hadoop?

Recommended is minimum of i3 processor, 20 GB disk and 4 GB RAM in order to learn Hadoop although students have learnt Hadoop on 2 GB RAM as well.

How this Hadoop course will help me in getting Big Data job?

Our training includes multiple workshops, POCs, project etc. that will prepare you to the level that you can start working from day 1 wherever you go. You will be assisted in resume preparation. The mock interview will help you in getting ready to face interviews. We will also guide you with the job openings matching to your resume. All this will help you in getting your dream Big Data job in the industry.

What will be the end result of doing this hadoop online course?

You will be skilled with the practical and theoretical knowledge that industry is looking for and will become certified Hadoop professional who is ready to take Big Data Projects in top organizations.

Where does DataFlair students come from?

DataFlair has blend of students from across the globe. Apart from India, we provide Hadoop training in US, UK, Singapore, Canada, UAE, France, Brazil, Ireland, Indonesia, Japan, Sri Lanka, etc to cover the complete globe.

How will I be able to interact with the instructor during training?

Both voice and chat will be enabled during the Big Data Hadoop training sessions. You can talk with the instructor or can also interact via chatting.

Is this Hadoop classroom training or online?

This is completely online training with a batch size of 8-10 students only. You will be able to interact with trainer through voice or chat and individual attention will be provided to all. The trainer ensures that every student is clear of all the concepts taught before proceeding ahead. So there will be complete environment of classroom learning.

Do you provide any Hadoop certification after training?

Yes, you will be provided DataFlair Certification. At the end of this course, you will work on a real time Project. Once you are successfully through the project, you will be awarded a certificate.

For further queries, how can I get in touch with you?

You can feel free to contact us by placing a CALL at +91 8451097879 OR dropping your queries on our email at info@data-flair.com

Why should I learn Hadoop?

Big data is the latest and the most demanding technology with continuously increasing demand in the Indian market and abroad. Hadoop professionals are among the highest paid IT professionals today with salary $135k (source: indeed job portal). You can check our blog related to Why should I learn Big Data?

What type of projects I will be doing during the training?

You will be doing real-time Hadoop projects in different domains like retail, banking, and finance, etc. using different technologies like Hadoop HDFS, MapReduce, Apache Pig, Apache Hive, Apache HBase, Apache Oozie, Apache Flume and Apache Sqoop.

Do you provide placement assistance?

The Hadoop course from DataFlair is 100% job oriented that will prepare you completely for interview and Big Data job perspective. Post Big Data course completion, we will provide you assistance in resume preparation and tips to clear Hadoop interviews. We will also let you know for Hadoop jobs across the globe matching your resume.

Can I attend a demo session before enrolling for Hadoop course?

Yes, you can attend the Hadoop demo class recording on our Big data Hadoop course page itself to understand the quality and level of Big Data training we provide and that creates the difference between DataFlair and other Hadoop online training providers.

Can you guide me about career of Big Data hadoop developer.

Hadoop is one of the hottest career options available today for all the software engineers to boost their professional career. In the US itself there are approximately 12,000 jobs currently for Hadoop developers and demand for Hadoop developers are increasing day by day rapidly far more than the availability.