Big Data & Hadoop

About Course

Traditional Data storage techniques can’t store or process large volume of structured and unstructured Data sets. Those data are referred as Big Data.  Hadoop on the other hand is a tool that is used to handle big data. It is an open-source framework manufactured by the Apache Software Foundation.

Affluenz IT Academy will emphasize on how to design distributed applications to manage “Big Data” using Hadoop. This will also detail how to use Pig and Spark to write scripts in order to process data sets on Hadoop cluster

Key Features

  1. 40 hours of instructor led online training
  2. Certificate of completion
  3. 2 Live Industry Project
  4. Dedicated awareness session from Industry experts

Online Classroom with virtual Internship

  • 3 Weeks’ course
  • 1 Week Live Project Internship
  • Certificate of completion
  • Certficate of Internship

9,999/-

Online Classroom with Corporate Internship

  • 6 Weeks course
  • 2 Weeks Live Project Internship
  • Certificate of completion
  • Certficate of Internship

14,999/-

Corporate Training

  • Self paced + Instructor Led classes
  • Flexible Pricing option

Why Big Data & Hadoop

According to IDC, by 2020, organizations that can analyze all relevant data and deliver actionable information will earn $430 billion more than their less analytically oriented peers. As of today, there is a surplus demand for people who are Hadoop 2.0 certified

Who should take this Big Data & Hadoop Course?

Affluenz IT Academy crafts this course to all who aspire to build a career in Big Data like Data Scientist, AI Engineer, Business Analyst, Information architect and so on. We recommend this course to

  • Developers aspiring to be a data scientist or machine learning engineer
  • Analytics managers who are leading a team of analysts 
  • Business analysts who want to understand data science techniques
  • Information architects who want to gain expertise in machine learning algorithms 
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in data science and machine learning
  • Experienced professionals who would like to harness machine learning in their fields to get more insights

Pre-requisites of Big Data & Hadoop

Participants in this online course should have:

  • Basic understanding on Data structure and Data Science
  • Basics of statistics and mathematics

4 Weeks Course

  1. Module 1: Introduction of Big Data
    • What is Big Data
    • Big Data Learning Techniques
    • 5C Architecture – connection, conversion, cyber cognition and configuration
  1. Module 2: Introduction to Hadoop
    • Basics of Hadoop
    • Hadoop Ecosystem
  1. Module 3: Hadoop components
    • 2.x Core Components
    • Hadoop Storage: HDFS (Hadoop Distributed File System)
    • Hadoop Processing: MapReduce Framework
  1. Module 4: Hadoop architecture and HDFS
    • Hadoop 2.x Cluster Architecture
    • Federation and High Availability Architecture
    • Typical Production Hadoop Cluster
    • Hadoop Cluster Modes
    • Common Hadoop Shell Commands
  1. Module 5: Live Project on Big Data & Hadoop
    • Assessment
    • Live Project
  1. Module 6: Certification & Closure
    • Certification of Completion
    • Review and Feedback

8 Weeks Course

  1. Module 1: Introduction of Big Data
    • What is Big Data
    • Big Data Learning Techniques
    • 5C Architecture – connection, conversion, cyber cognition and configuration
  1. Module 2: Introduction to Hadoop
    • Basics of Hadoop
    • Hadoop Ecosystem
  1. Module 3: Hadoop components
    • 2.x Core Components
    • Hadoop Storage: HDFS (Hadoop Distributed File System)
    • Hadoop Processing: MapReduce Framework
  1. Module 4: Hadoop architecture and HDFS
    • Hadoop 2.x Cluster Architecture
    • Federation and High Availability Architecture
    • Typical Production Hadoop Cluster
    • Hadoop Cluster Modes
    • Common Hadoop Shell Commands
    • Hadoop 2.x Configuration Files
    • Single Node Cluster & Multi-Node Cluster set up
    • Basic Hadoop Administration
  1. Module 5: Hadoop MapReduce Framework
    • Traditional way vs MapReduce way
    • Why MapReduce
    • YARN Components
    • YARN Architecture
    • YARN MapReduce Application Execution Flow
    • YARN Workflow
    • Anatomy of MapReduce Program
    • Input Splits, Relation between Input Splits and HDFS Blocks
    • MapReduce: Combiner & Partitioner
    • Demo of Health Care Dataset
    • Demo of Weather Dataset
  1. Module 6: Live Project on Big Data & Hadoop
    • Assessment
    • Live Project
  1. Module 7: Certification & Closure
    • Certification of Completion
    • Internship Certificate
    • Review and Feedback

Sample Certification

  • Certificate of Completion
  • Internship Certificate

Your Future Starts Here.