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iClass Training in Noida India

Hadoop Training Noida Benefits

  • Real Time Trainers
  • 100% Placement
  • Small Training Batch
  • Flexible Timings
  • Practical Guidance
  • Excellent Lab Facility
  • Hadoop Resume Preparation
  • Hands on Experience
  • apache hadoop Certification Support

 

apache hadoop Training Support

Enquiry : +91 9672234513

Enquiry : +91 9672234514

 

Hadoop training Noida Reviews

Hadoop training Noida
Reviewed by
Vaikuntanath
on
Hi this is Vaikuntanath from Noida. After my admission continiously 3 days class were not conducted so I became feared. At 4th day one faculty came and after one mont I realised that my subject became very easier. I really very thanful for this .

Rating:
5/5 5 Star Rating: Excellent

Hadoop training Noida
Reviewed by
Aashish
on
iClass Training Noida in Sector 33 was a very good experience and managed to gain a lot of knowledge in this SAP QM certification field. Thank you for iClass Training Noida in Noida, providing me such a good environment along with real-time work experience throughout the completion of course.

Rating:
5/5 5 Star Rating: Excellent

Hadoop training Noida
Reviewed by
Deviprasad
on
I am Deviprasad and done dot net course. I am very thankful for iClass Training Noida to help me out for dot net course completation. I am very weak at the time of entry but now I think I am a king of my subject.

Rating:
5/5 5 Star Rating: Excellent

Hadoop training Noida
Reviewed by
Vasudev
on
In iClass Training Noida in Sector 2 centre quality of teaching is nice and I got the practical exposure to write my own programs. Cost wise it is very less and its truly knowledge and job oriented course. I would recommend iClass Training Noida in Noida for SAP BASIS certification.

Rating:
4/5 4 Star Rating: Very Good

Hadoop training Noida
Reviewed by
Rajkumari
on
I was a fresher when I joined iClass Training Noida in Noida.I found that they follow an advanced syllabus for Oracle with the best trainers in xrarea centre. Nice positive environment to learn and very open to clear the doubts. For people who are seeking knowledge here is the place to go.

Rating:
5/5 5 Star Rating: Excellent

Hadoop training Noida
Reviewed by
Lakshmishree
on
iClass Training Noida in Sector 57 is a best place in Noida to learn sap dynpro course. The training is awesome and the trainers are well knowledged.

Rating:
4/5 4 Star Rating: Very Good

Best Hadoop training institute in noida

Hadoop Training in Noida & Best Hadoop Bigdata Administration Training Institute in Noida

4 Star Rating: Very Good 4.3 out of 5 based on 3398 student ratings.

iClass Noida provides real-time and placement focused apache hadoop training in noida . Our hadoop administration course includes basic to advanced level and our apache hadoop course is designed to get the placement in good MNC companies in noida as quickly as once you complete the big data hadoopv certification training course. Our apache hadoop trainers are hadoop administration certified experts and 8 years experienced working professionals with hands on real time multiple Hadoop projects knowledge. We have designed our apache hadoop course content and syllabus based on students requirement to achieve everyone's career goal.

iClass Noida offers apache hadoop training with choice of multiple training locations across noida. Our hadoop administration training centers are equipped with lab facilities and excellent infrastructure. We also provide hadoop administration certification training path for our students in noida. Through our associated apache hadoop training centers, we have trained more than 3554 apache hadoop students and Placement provided for 2692 students. Our hadoop administration course fee is value for money and tailor-made course fee based on the each student's training requirements. apache hadoop training in noida conducted on day time classes, weekend training classes, evening batch classes and fast track training classes.

Hadoop training course content and Syllabus in Noida

Hadoop Course Content
  • Hadoop Overview, Architecture Considerations, Infrastructure, Platforms and Automation

Use case walkthrough
  • ETL
  • Log Analytics
  • Real Time Analytics

Hbase for Developers :

NoSQL Introduction
  • Traditional RDBMS approach
  • NoSQL introduction
  • Hadoop & Hbase positioning

Hbase Introduction
  • What it is, what it is not, its history and common use-cases
  • Hbase Client Shell, exercise

Hbase Architecture
  • Building Components
  • Storage, B+ tree, Log Structured Merge Trees
  • Region Lifecycle
  • Read/Write Path

Hbase Schema Design
  • Introduction to hbase schema
  • Column Family, Rows, Cells, Cell timestamp
  • Deletes
  • Exercise - build a schema, load data, query data

Hbase Java API Exercises
  • Connection
  • CRUD API
  • Scan API
  • Filters
  • Counters
  • Hbase MapReduce
  • Hbase Bulk load

Hbase Operations, cluster management
  • Performance Tuning
  • Advanced Features
  • Exercise
  • Recap and Q&A

MapReduce for Developers

Introduction
  • Traditional Systems / Why Big Data / Why Hadoop
  • Hadoop Basic Concepts/Fundamentals

Hadoop in the Enterprise
  • Where Hadoop Fits in the Enterprise
  • Review Use Cases

Architecture
  • Hadoop Architecture & Building Blocks
  • HDFS and MapReduce

Hadoop CLI
  • Walkthrough
  • Exercise

MapReduce Programming
  • Fundamentals
  • Anatomy of MapReduce Job Run
  • Job Monitoring, Scheduling
  • Sample Code Walk Through
  • Hadoop API Walk Through
  • Exercise

MapReduce Formats
  • Input Formats, Exercise
  • Output Formats, Exercise

Hadoop File Formats

MapReduce Design Considerations

MapReduce Algorithms
  • Walkthrough of 2-3 Algorithms

MapReduce Features
  • Counters, Exercise
  • Map Side Join, Exercise
  • Reduce Side Join, Exercise
  • Sorting, Exercise

Use Case A (Long Exercise)
  • Input Formats, Exercise
  • Output Formats, Exercise

MapReduce Testing

Hadoop Ecosystem
  • Oozie
  • Flume
  • Sqoop
  • Exercise 1 (Sqoop)
  • Streaming API
  • Exercise 2 (Streaming API)
  • Hcatalog
  • Zookeeper

HBase Introduction
  • Introduction
  • HBase Architecture

MapReduce Performance Tuning

Development Best Practice and Debugging

Apache Hadoop for Administrators

Hadoop Fundamentals and Architecture
  • Why Hadoop, Hadoop Basics and Hadoop Architecture
  • HDFS and Map Reduce

Hadoop Ecosystems Overview
  • Hive
  • Hbase
  • ZooKeeper
  • Pig
  • Mahout
  • Flume
  • Sqoop
  • Oozie

Hardware and Software requirements
  • Hardware, Operating System and Other Software
  • Management Console

Deploy Hadoop ecosystem services
  • Hive
  • ZooKeeper
  • HBase
  • Administration
  • Pig
  • Mahout
  • Mysql
  • Setup Security

Enable Security Configure Users, Groups, Secure HDFS, MapReduce, HBase and Hive
  • Configuring User and Groups
  • Configuring Secure HDFS
  • Configuring Secure MapReduce
  • Configuring Secure HBase and Hive

Manage and Monitor your cluster

Command Line Interface

Troubleshooting your cluster

Introduction to Big Data and Hadoop

Hadoop Overview
  • Why Hadoop
  • Hadoop Basic Concepts
  • Hadoop Ecosystem MapReduce, Hadoop Streaming, Hive, Pig, Flume, Sqoop, Hbase, Oozie, Mahout
  • Where Hadoop fits in the Enterprise
  • Review use cases

Apache Hive & Pig for Developers

Overview of Hadoop
  • Big Data and the Distributed File System
  • MapReduce

Hive Introduction
  • Why Hive?
  • Compare vs SQL
  • Use Cases

Hive Architecture Building Blocks
  • Hive CLI and Language (Exercise)
  • HDFS Shell
  • Hive CLI
  • Data Types
  • Hive Cheat-Sheet
  • Data Definition Statements
  • Data Manipulation Statements
  • Select, Views, GroupBy, SortBy/DistributeBy/ClusterBy/OrderBy, Joins
  • Built-in Functions
  • Union, Sub Queries, Sampling, Explain

Hive Usecase implementation - (Exercise)
  • Use Case 1
  • Use Case 2
  • Best Practices

Advance Features
  • Transform and Map-Reduce Scripts
  • Custom UDF
  • UDTF
  • SerDe
  • Recap and Q&A

Pig Introduction
  • Position Pig in Hadoop ecosystem
  • Why Pig and not MapReduce
  • Simple example (slides) comparing Pig and MapReduce
  • Who is using Pig now and what are the main use cases
  • Pig Architecture
  • Discuss high level components of Pig
  • Pig Grunt - How to Start and Use

Pig Latin Programming
  • Data Types
  • Cheat sheet
  • Schema
  • Expressions
  • Commands and Exercise
  • Load, Store, Dump, Relational Operations,Foreach, Filter, Group, Order By, Distinct, Join, Cogroup,Union, Cross, Limit, Sample, Parallel

Use Cases (working exercise)
  • Use Case 1
  • Use Case 2
  • Use Case 3 (compare pig and hive)

Advanced Features, UDFs

Best Practices and common pitfalls

Mahout & Machine Learning
  • Mahout Overview
  • Mahout Installation
  • Introduction to the Math Library
  • Vector implementation and Operations (Hands-on exercise)
  • Matrix Implementation and Operations (Hands-on exercise)
  • Anatomy of a Machine Learning Application

Classification
  • Introduction to Classification
  • Classification Workflow
  • Feature Extraction
  • Classification Techniques (Hands-on exercise)

Evaluation (Hands-on exercise)
  • Clustering
  • Use Cases
  • Clustering algorithms in Mahout
  • K-means clustering (Hands-on exercise)
  • Canopy clustering (Hands-on exercise)

Clustering
  • Mixture Models
  • Probabilistic Clustering Dirichlet (Hands-on exercise)
  • Latent Dirichlet Model (Hands-on exercise)
  • Evaluating and Improving Clustering quality (Hands-on exercise)
  • Distance Measures (Hands-on exercise)

Recommendation Systems
  • Overview of Recommendation Systems
  • Use cases
  • Types of Recommendation Systems
  • Collaborative Filtering (Hands-on exercise)
  • Recommendation System Evaluation (Hands-on exercise)
  • Similarity Measures
  • Architecture of Recommendation Systems
  • Wrap Up

Hadoop training duration in Noida

Regular Classes( Morning, Day time & Evening)

  • Duration : 4 weeks

Weekend Training Classes( Saturday, Sunday & Holidays)

  • Duration : 5 Weeks

Fast Track Training Program( 2+ hours classes daily)

  • Duration : within 2 weeks

Hadoop trainer Profile & Placement

Our Hadoop Trainers

  • More than 8 Years of experience in Hadoop Technologies
  • Has worked on 8 realtime Hadoop projects
  • Working in a MNC company in Noida
  • Trained 3554+ Students so far.
  • Strong Theoretical & Practical Knowledge
  • Hadoop certified Professionals

Hadoop (hadoop administration) Placement Training in Noida

  • More than 3554+ students Trained
  • 2692 students Placed
  • 1635 Interviews Organized
  • Placement Supported by InterviewDesk.com

Hadoop training Locations in Noida

Our Hadoop Bigdata Administration Training centers

  • Bajidpur
  • Bisrakh Jalalpur
  • Dadri Road
  • Deri Skaner
  • Ecotech III
  • Greater Noida
  • Habibpur
  • Ithaira
  • kharkhoda
  • Maincha
  • Makora
  • Malakpur
  • Noida
  • Rithori
  • Secotor 62
  • Sector 25
  • Shahpur
  • Surajpur
  • Vaidpura

Hadoop training batch size (students per class) in Noida

Regular Batch ( Morning, Day time & Evening)

  • Seats Available : 6 (maximum)

Weekend Training Batch( Saturday, Sunday & Holidays)

  • Seats Available : 9 (maximum)

Fast Track batch

  • Seats Available : 5 (maximum)

Upcmoing apache hadoop Training Classes in Noida

    Below are start date of hadoop training classes in Noida with course start date, class timings, morning / evening / weekend training sessions along with total seats and available seats. To rigister or enuqire, Just give a missed call to 9672234513 anytime.

    Start DateCourse TimingsSeats & AvailabilityRegistration Status
    15-Jul-20209.00 AM till 12.00 PM
    Fasttrack Class
    Total :5
    Available: 4
    Booking Open
    18-Jul-202010.00 AM till 4.00 PM (Sat & Sunday Only)
    Weekend Class
    Total :4
    Available: 3
    Booking Open
    19-Jul-202010.00 AM till 4.00 PM (Sat & Sunday Only)
    Weekend Class
    Total :4
    Available: 3
    Booking Open
    24-Jul-20207.00 PM till 8.30 PM
    Evening Class
    Total :5
    Available: 5
    Booking Open
    29-Jul-20207.00 PM till 8.30 PM
    Evening Class
    Total :5
    Available: 4
    Booking Open
    29-Jul-20207.30 AM till 9.00 AM
    Morning Class
    Total :6
    Available: 5
    Booking Open

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