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Hadoop Training Institutes in Bangalore

Best Hadoop Training in Bangalore

Hadoop Training in Marathahalli & Best Hadoop Training Institutes in Bangalore

Best Hadoop training institute Ecare technologies Marathahalli, Bangalore, provides real-time and placement oriented Hadoop training in Bangalore. Ecare technologies provide the Best Hadoop training courses in Bangalore. Ecare Hadoop training course content is designed from basics to advanced levels. We have a team of Hadoop experts who are working professionals with hands-on real-time Hadoop projects knowledge, which will give students an edge over other Training Institutes. Hadoop training course content is designed to get the placement in major MNC companies in Bangalore as soon as you complete the Hadoop training course.

Best Hadoop training institute in Bangalore focuses on the needs of the Hadoop community. Ecare technologies listed one of the top Hadoop training institutes in Bangalore. We offer Hadoop education for working professionals. Hadoop training in Bangalore understands the need of Hadoop community. We offer all Hadoop training courses as students option. Ecare technologies provide free Hadoop training materials of soft copy and hard copy. Discover best Hadoop training in Bangalore at Ecare technologies.
Our Hadoop training courses help to students to get placement immediately after course completion. Our practical, real-time Hadoop project scenarios training helps to work on Hadoop projects. Our Hadoop training program helps every student to achieve their goal in Hadoop career.

Best Training Institute, Ecare technologies, Marathahalli, Bangalore offers training with choice of multiple training locations across Bangalore. Ecare technologies Hadoop training centers are having Best lab facilities and excellent infrastructure. We have successfully trained and provided placement for many of our Trained Hadoop students, Hadoop training course fee is very economical compared to other Training Institutes In Bangalore.

Hadoop Training In Bangalore, Ecare technologies provide regular training classes, Morning Batches, Evening Batches, weekend training classes and fast-track training classes for Hadoop. Ecaretechnologies provides online and Corporate training classes for Hadoop.


Hadoop Training Syllabus in Bangalore

Hadoop training course content and Syllabus in Bangalore
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


Popular Interview Questions for Hadoop Training

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Hadoop Training trainer Profile & Placement

  • More than 10 Years of experience in Hadoop Training
  • Has worked on multiple realtime Hadoop Training
  • Working in a top MNC company in Bangalore
  • Trained 2000+ Students so far in Hadoop Training.
  • Strong Theoretical & Practical Knowledge
  • Certified Professionals

Hadoop Training Placement in Bangalore

  • More than 2000+ students Trained in Hadoop Training
  • 92% percent Placement Record
  • 1000+ Interviews Organized

Hadoop Training batch size in Bangalore


Regular Batch ( Morning, Day time & Evening)

  • Seats Available : 8 (maximum)

Hadoop Training Weekend Training Batch( Saturday, Sunday & Holidays)

  • Seats Available : 8 (maximum)

Hadoop Training Fast Track batch

  • Seats Available : 5 (maximum)

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Hadoop Training Reviews

Hadoop Training in Bangalore - Marathahalli
Ecare Technologies

4.9 out of 5
based on 6284 ratings.

This is to inform you that I got my friend enrolled into your training institute for Hadoop Training Weekend Class 8:00 AM to 10:00 AM and the training started from 22nd august 2016.It was supposed to be of 45 hours course with a live project. 45 hours means 11 to 12 weeks course.But its just been 2 month (10 weeks i.e 40 hours) and I came to know that today (Sunday 23rd october 2016) - the trainer has informed that the course is complete and next weekend they will have final test. Thereafter, they can contact the trainer if they have any questions - on need basis. Excellent hands on was conducted and live project was done.I am so happy with your support sir, 15,000/- we paid for my friend and this is best institute for hadoop at Marathalli.. The hadoop trainer here is giving best and giving Excellent name to the institute. Certification support is very good.


Nitin


 

ecare technologies marathalli is awesome institute for Hadoop.The way Hadoop sir teach is easy to understand and easy learning,with good clarity about the subject knowledge along with practical examples.Earlier i was not good in langauage part i.e JAVA,bt after attending the class i become more confident about this.He provide proper guidelines for every problem if we have.In other words we can say that he is good trainer.


Kiran


 

Before joining e care technologies my knowledge was limited related IT Hadoop Bigdata technologies. But now after joining ecare my Hadoop knowledge has improved a lot. I learnt how Database Management is developed in real-time environment. Also learnt how to face an interview questions in Hadoop. In my personal opinion my thinking has completely changed towards IT industry after joining ecare technologies marathalli


Madhusudhan