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  • Work on Industry-specific Use-cases which can be showcased to future recruiters
  • Weekly mock interviews / group discussions / interview related questions.
  • Highly-Configured Computers for practice.
  • Guidance and Tips for portfolio, interviews, resume, etc.
  • Resume & Interviews Preparation Support
  • Become CCP Data Engineer Certified Professional

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Best Big Data Hadoop Tools Covered

Hadoop Developer

Hadoop Administrator

Spark & Scala

Apache Hbase

Flume, Sqoop


Amazon Web Services

HDFS Architecture

MapReduce, Hive

PIG & Oozie

JAVA Essentials


Python for Hadoop

Mysql Database



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Become a Certified Hadoop Developer.

100% Placement Program

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  • Career guidance and support
  • Industry-driven comprehensive curriculum
  • Practical oriented / Job oriented Training
  • Will make your Resume Ready as per Job Requirements
  • Conducted Mock Test
  • Mock Interviews Conducted
  • Average Salary of Big Data Hadoop Developers is $135,000 ( salary data)

Course Duration

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  • 60 Hrs of Theory & Lab Sessions
  • Daily Classes for freshers
  • Saturday & Sunday Classes for working Employees
  • Certification in Hadoop
  • Back up Classes
  • Free Technical Support even after course completion
  • Lab Facility and Study Materials

Main Topics covered

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  • Big Data
  • Hadoop Admin and Developer
  • Spark and Scala
  • Hadoop with Python & Java
  • Hadoop Common
  • Hadoop Distributed File System (HDFS™)
  • Hadoop YARN, MapReduce
  • Ozone, Submarine
  • Cassandra, HBase
  • Hive, Pig, Mahout, ZooKeeper
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Learn by Working on Real Time Hadoop Projects

Project 1

  • Industry: Media & Entertainment
  • Project 2

  • Industry: Social Media and Travel
  • Project 3

  • Industry: Banking and Finance
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    About Hadoop Trainer

    Mr. shivank BigData Hadoop Expert

    Cloudera Certified Spark and Hadoop Developer, having 8+ years of IT-industry experience
    Passion for learning and teaching new technologies
    Strong knowledge on distributions like Cloudera, Hortonworks
    Strong knowledge on Hadoop ecosystem components Hive, Pig, Mapreduce, Hcatalog, Sqoop, Sqoop2, Oozie, Impala, HDFS, Spark, Kafka and Storm.
    Strong knowledge on shell scripting and SQL.
    Hands on experience on Hive, Pig, MapReduce, Sqoop, Sqoop2, Oozie.
    Good exposure on relational database (Oracle,SQL) and No SQl database(Mango DB and Cassandra)
    Having Proficiency with Data warehousing, UNIX, SQL, PL/SQL, and Core Java.

    Why get Hadoop certified Professional

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    Getting certified shows employers that you have a clear understanding of the core concepts of Hadoop. You can also add the qualification to your CV, and easily upload it to your LinkedIn profile.

    Becoming certified shows you’ve got genuine Hadoop skills, and that you are motivated to learn: two essential qualities in today’s business world. Demonstrating these qualities can help improve your chances of finding the job you want.

    Improving your Hadoop knowledge can help you find a job, get promoted, or start a whole new career.

    Hadoop Certification Training in Chennai, Big Data Courses Velachery, OMR , Anna Nagar, T-Nagar

    Please be informed that we are conducting a FREE DEMO CLASS on Tomorrow in chennai Institute for Advanced Hadoop Training. Call 9840021877 ,9620420487,080-42024661 and Book your Seat Now!


    Popular BigData Hadoop Modules you need to learn for Better Placement Opportunities

    Introduction to Data Science

    Big Data & Hadoop Training Course is designed to enhance your knowledge and skills to become a successful Hadoop Developer. You will gain knowledge of core concepts of Big Data & Hadoop along with implementation of various industry related case studies.

    Hadoop Administrator Classes

    Installing, managing, monitoring, advanced operations, security, governance, certification

    Data Analytics Classes

    SQL, scripting languages, machine learning, Big Data analytics, certification

    what is Big Data

    Big Data Analytics is "the process of examining large data sets containing a variety of data types.Big Data Analytics tools also help businesses save time and money and aid in gaining insights to inform data-driven decisions by data scientists.

    Apache spark & scala

    A fast and general compute engine for Hadoop data. Spark provides a simple and expressive programming model that supports a wide range of applications, including ETL, machine learning, stream processing, and graph computation.

    Python for Hadoop

    Hadoop framework is written in Java language, but it is entirely possible for Hadoop programs to be coded in Python or C++ language

    Java for Hadoop

    learn java essentials for hadoop right from the basics of Arrays in Java and cover all the core java basics required to become a productive Hadoop developer


    A YARN-based system for parallel processing of large data sets.


    A distributed file system that provides high-throughput access to application data.


    Hive is a data warehouse infrastructure tool to process structured data in Hadoop. It resides on top of Hadoop to summarize Big Data, and makes querying and analyzing easy.


    Apache Oozie is a Java Web application used to schedule Apache Hadoop jobs. Oozie combines multiple jobs sequentially into one logical unit of work


    Sqoop is a tool for transferring data between Hadoop & relational databases


    Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming data into the Hadoop Distributed File System (HDFS)


    A scalable, distributed database that supports structured data storage for large tables.


    A high-level data-flow language and execution framework for parallel computation

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    Module 1

    • Big Data Introduction
    • Hadoop Introduction
    • What is Hadoop? Why Hadoop?
    • Hadoop History?
    • Different types of Components in Hadoop?
    • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
    • What is the scope of Hadoop?

    Deep Drive in HDFS (for Storing the Data):-

    • Introduction of HDFS
    • HDFS Design
    • HDFS role in Hadoop
    • Features of HDFS
    • Daemons of Hadoop and its functionality
    • Name Node
    • Secondary Name Node
    • Job Tracker
    • Data Node
    • Task Tracker
      • Anatomy of File Wright
      • Anatomy of File Read
      • Network Topology
    • Nodes
    • Racks
    • Data Center
      • Parallel Copying using DistCp
      • Basic Configuration for HDFS
      • Data Organization
    • Blocks and
    • Replication
      • Rack Awareness
      • Heartbeat Signal
      • How to Store the Data into HDFS
      • How to Read the Data from HDFS
      • Accessing HDFS (Introduction of Basic UNIX commands)
      • CLI commands


    MapReduce using Java (Processing the Data):-

    • The introduction of MapReduce.
    • MapReduce Architecture
    • Data flow in MapReduce
      • Splits
      • Mapper
      • Portioning
      • Sort and shuffle
      • Combiner
      • Reducer
    • Understand Difference Between Block and InputSplit
    • Role of RecordReader
    • Basic Configuration of MapReduce
    • MapReduce life cycle
      • Driver Code
      • Mapper
      • and Reducer
    • How MapReduce Works
    • Writing and Executing the Basic MapReduce Program using Java
    • Submission & Initialization of MapReduce Job.
    • File Input/Output Formats in MapReduce Jobs
      • Text Input Format
      • Key Value Input Format
      • Sequence File Input Format
      • NLine Input Format
    • Joins
      • Map-side Joins
      • Reducer-side Joins
    • Word Count Example
    • Partition MapReduce Program
    • Side Data Distribution
      • Distributed Cache (with Program)
    • Counters (with Program)
      • Types of Counters
      • Task Counters
      • Job Counters
      • User Defined Counters
      • Propagation of Counters
    • Job Scheduling

    Module 2

    • Linux commands
    • Single and Multinode cluster installation (HADOOP Gen 2)
    • AWS (EC2, RDS, S3, IAM and Cloud formation)
    • Cloudera and Hortonworks distribution installation on AWS
    • Cloudera Manager and Ambari
    • Hadoop Security and Commissioning and Decommissioning of nodes
    • Sizing of Hadoop Cluster and Name Node High Availability

    Module 5

    • An Introduction to Python
    • 1.1 Brief about the course
    • 1.2 History/timelines of python
    • 1.3 What is python ?
    • 1.4 What python can do?
    • 1.5 How the name was put up as python
    • 1.6 Why python?
    • 1.7 Who all are using python
    • 1.8 Features of python
    • 1.9 Python installation
    • 1.10. Hello world
    • 1. using cmd
    • 2. IDLE
    • 3. By py script
    • 4. python command line
    • 2: Beginning Python Basics
    • 2.1. The print statements
    • 2.3. Python Data Structures
    • 2.4. variables & Data Types
    • 1. rules for variable
    • 2. declaring variables
    • 3. Assignment in variables
    • 4. operations with variables
    • 5. Reserved keyword
    • 2.5. Operators in Python
    • 2.6. Simple Input & Output
    • 2.7. Examples for variables , Data Types ,operators
    • 3: Python Program Flow
    • 3.1. Indentation
    • 3.2. The If statement and its' related statement
    • 3.3. An example with if and it's related statement
    • 3.4. The while loop
    • 3.5. The for loop
    • 3.6. The range statement
    • 3.7. Break
    • 3.8. Continue
    • 3.9. pass
    • 3.9. Examples for looping
    • 4: Functions & Modules
    • 4.1. system define function(number system and its sdf ,String and its sdf
    • )
    • 4.2. Create your own functions (user define function)
    • 4.3. Functions Parameters
    • 4.4. Variable Arguments
    • 4.5. An Exercise with functions
    • 5: Exceptions
    • 5.1. Errors
    • 5.2. Exception Handling with try
    • 5.3. Handling Multiple Exceptions
    • 5.4. raise
    • 5.5. finally
    • 5.6. else
    • 6: File Handling
    • 6.1. File Handling Modes
    • 6.2. Reading Files
    • 6.3. Writing & Appending to Files
    • 6.4. Handling File Exceptions
    • 7: Data Structures and Data Structures functions
    • 7.1. List and its sdf
    • 7.2. tuple and its sdf
    • 7.3. Dictionary and its sdf
    • 7.4. set and its sdf
    • 7.5. use cases and practical examples
    • 8: casting
    • 8:1 intro to casting

    Module 3

    • HIVE:-

      • Introduction tHIVE
      • HIVE Meta Store
      • HIVE Architecture
      • Tables in HIVE
        • Managed Tables
        • External Tables
      • Hive Data Types
        • Primitive Types
        • Complex Types
      • Partition
      • Joins in HIVE
      • HIVE UDF’s and UADF’s with Programs
      • Word Count Example


      • Introduction tHBASE
      • Basic Configurations of HBASE
      • Fundamentals of HBase
      • What is NoSQL?
      • HBase Data Model
        • Table and Row
        • Column Family and Column Qualifier
        • Cell and its Versioning
      • Categories of NoSQL Data Bases
        • Key-Value Database
        • Document Database
        • Column Family Database
      • HBASE Architecture
        • HMaster
        • Region Servers
        • Regions
        • MemStore
        • Store
      • SQL vs. NOSQL
      • How HBASE is differed from RDBMS
      • HDFS vs. HBase
      • Client-side buffering or bulk uploads
      • HBase Designing Tables
      • HBase Operations
        • Get
        • Scan
        • Put
        • Delete


      • What is MongoDB?
      • Where tUse?
      • Configuration On Windows
      • Inserting the data intMongoDB?
      • Reading the MongoDB data.

      Cluster Setup:–

      • Downloading and installing the Ubuntu12.x
      • Installing Java
      • Installing Hadoop
      • Creating Cluster
      • Increasing Decreasing the Cluster size
      • Monitoring the Cluster Health
      • Starting and Stopping the Nodes

    Hadoop Training Benefits for

    STUDENTS, Freshers, Job Seekers




    Java/ Hadoop Developer

    Hands on Java Programming Expertise (Core Java, J2EE) • Scala is a Big plus • Hands on Building Restful Services. • Hands on experience working on Big Data Technologies (Any of MapReduce/Spark Streaming/ Kafka) • Experience working on SQL,NoSQL solutions with clear understanding of pros and cons of both relational & Free form databases. • Knowledge and a particular interest in issues related to Big Data, large scale distributed stream processing, realtime computation systems and behavioral analytics. • Ability to determine impact of architectural solutions and come up with Recommendations

    Sampoorna Consultants

    Job Description (Hadoop Developer ML/TL Chennai)

    Shifts: UK Shifts Job Location: Chennai • Must have good experience on the following:

    Familiarity with Hadoop ecosystem and its components.

    Expertise knowledge of HDFS, Hadoop, Hive, HBase, and Pig.

    Experience of writing MapReduce jobs . Hands on experience in HiveQL. Familiarity with data loading tools such as Flume, Sqoop etc. Familiarity with the schedulers


    HADOOP DEVELOPER 1 - 3 Years

    Key Responsibilities : 1 - 3 years of experience in Python programming language required 2 - 2 years of experience in Scala programming language required 3 Should be Proficient in using relational databases and writing SQL 4 AWS Experience in AWS ecosystem tools S3/Athena/ Cloud Formation/ EC2 5 Strong understanding and experience with functional and object-oriented design and development in Python or Scala 6 Shift 12 PM to 10 PM.Read More


    Job Description (Hadoop developer)

    SkillSet: sql, hive, unix, spark, scala. Hands on experience in Hadoop Platform Tools. Experince in Hadoop Spark Nifi Unix Hive Control M Scripting Shell Scala PL SQL Primary Skill: Hadoop ,

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    Where do the classes take place?

    Classes will be Both Classroom & Live Instructor-led online. The online interface lets you and the Trainer have a 1-to-1 interaction. It's more effective and as same as sitting in a physical classroom.

    What if i miss the classes?

    Whats New in Inventateq about Hadoop?

    Will i get Technical Support after completion of course?

    Will i Get FREE Demo Class before i pay Fees?

    Hadoop Courses in other cities

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    Do you provide Placements?

    Yes, We do provide Placements Support. We have Dedicated placement Officer taking care of the Students placement. Over and above we have tie-ups with so many IT Companies where the prospective HRs and Employers contact us for placements & internships. you are updated on various job opportunities for big data hadoop in Bangalore and Chennai and depending upon your interest in those your resumes are shared and the process is taken ahead

    Do We Get To Work On Live Projects?

    The entire Big Data Hadoop training has been built around Real Time Implemenation, You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio, GitHub repository and Showcase to Recruiters in Interviews & Get Placed

    Will i Get Technical Support Even after Completion of Course?

    Yes, You can Ask any technical Doubts/Question to Trainer and get Clarify, Even you can Reattend Classes for the topics you want Revision. While Pursing, You should complete your course sincerely by doing Assignments Regularly given by trainer.

    What all certifications you provide?

    We provide industry recognized certifications which are:
    • Certified Big Data Hadoop Developer

    Who are the Trainers?

    Our Trainers are chosen not only for their knowledge and expertise but also for their real-world experience in the field they teach. We Will Help you Get Resume Ready and Provided Interview