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iClass Training in Surat India

Hadoop Training Surat 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 Surat Reviews

Hadoop training Surat
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on
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Rating:
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Best Hadoop training institute in surat

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

4 Star Rating: Very Good 4.6 out of 5 based on 3253 student ratings.

iClass Surat provides real-time and placement focused apache hadoop training in surat . 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 surat as quickly as once you complete the big data hadoopv certification training course. Our apache hadoop trainers are hadoop administration certified experts and 9 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 Surat offers apache hadoop training with choice of multiple training locations across surat. 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 surat. Through our associated apache hadoop training centers, we have trained more than 3309 apache hadoop students and Placement provided for 2460 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 surat conducted on day time classes, weekend training classes, evening batch classes and fast track training classes.

Hadoop training course content and Syllabus in Surat

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 Surat

Regular Classes( Morning, Day time & Evening)

  • Duration : 7 weeks

Weekend Training Classes( Saturday, Sunday & Holidays)

  • Duration : 8 Weeks

Fast Track Training Program( 4+ hours classes daily)

  • Duration : within 4 weeks

Hadoop trainer Profile & Placement

Our Hadoop Trainers

  • More than 9 Years of experience in Hadoop Technologies
  • Has worked on 12 realtime Hadoop projects
  • Working in a MNC company in Surat
  • Trained 3309+ Students so far.
  • Strong Theoretical & Practical Knowledge
  • Hadoop certified Professionals

Hadoop (hadoop administration) Placement Training in Surat

  • More than 3309+ students Trained
  • 2460 students Placed
  • 1548 Interviews Organized
  • Placement Supported by InterviewDesk.com

Hadoop training Locations in Surat

Our Hadoop Bigdata Administration Training centers

  • Ghod Dhod Road
  • Ring Road
  • Timaliawad
  • Surat Railway station
  • Station Road
  • Rander
  • Udhana
  • Puna
  • Bardoli
  • Chalthan

Hadoop training batch size (students per class) in Surat

Regular Batch ( Morning, Day time & Evening)

  • Seats Available : 7 (maximum)

Weekend Training Batch( Saturday, Sunday & Holidays)

  • Seats Available : 11 (maximum)

Fast Track batch

  • Seats Available : 5 (maximum)

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