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

  • 40 hours of instructor led online training
  • Certificate of completion
  • 2 Live Industry Project
  • 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

9999/-

Online Classroom with Corporate Internship

  • 6 Weeks’ course
  • 2 Week 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?

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

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

Course Preview

4 Weeks Course

  • Module 1: Introduction of Big Data

                 1a> What is Big Data

                 1b> Big Data Learning Techniques

                  1c> 5C Architecture – connection, conversion, cyber cognition and configuration

  • Module 2: Introduction to Hadoop

                 2a> Basics of Hadoop

                 2b> Hadoop Ecosystem

                  2c> 5C Architecture – connection, conversion, cyber cognition and configuration

  • Module 3: Hadoop components

                 3a> 2.x Core Components

                 3b> Hadoop Storage: HDFS (Hadoop Distributed File System)

                  3c> Hadoop Processing: MapReduce Framework

  • Module 4: Hadoop architecture and HDFS

                 4a> Hadoop 2.x Cluster Architecture

                 4b> Federation and High Availability Architecture

                  4c> Typical Production Hadoop Cluster

                  4d> Hadoop Cluster Modes

 

                  4e> Common Hadoop Shell Commands

  • Module 5: Live Project on Big Data & Hadoop

                    5a> Assessment

                    5b> Live Project

  • Module 6: Certification & Closure

                    6a> Certification of Completion

                    6b> Review and Feedback

           8 Weeks Course

  • Module 1: Introduction of Big Data

                 1a> What is Big Data

                 1b> Big Data Learning Techniques

                  1c> 5C Architecture – connection, conversion, cyber cognition and configuration

  • Module 2: Introduction to Hadoop

                    2a> Basics of Hadoop

                     2b> Hadoop Ecosystem

  • Module 3: Hadoop components

                      3a> 2.x Core Components

                      3b> Hadoop Storage: HDFS (Hadoop Distributed File System)

                       3c> Hadoop Processing: MapReduce Framework

  • Module 4: Advanced Hadoop architecture and HDFS

                         4a> Hadoop 2.x Cluster Architecture

                          4b> Federation and High Availability Architecture

                           4c> Typical Production Hadoop Cluster

                         4d> Hadoop Cluster Modes

                         4e> Common Hadoop Shell Commands

                         4f> Hadoop 2.x Configuration Files

                         4g> Single Node Cluster & Multi-Node Cluster set up

                         4h> Basic Hadoop Administration

  • Module 5: Hadoop MapReduce Framework

                         5a> Traditional way vs MapReduce way

                         5b> Why MapReduce

                         5c> YARN Components

                         5d> YARN Architecture

                         5e> YARN MapReduce Application Execution Flow

                         5f> YARN Workflow

                         5g> Anatomy of MapReduce Program

                         5h> Input Splits, Relation between Input Splits and HDFS Blocks

                         5i> MapReduce: Combiner & Partitioner

                         5j> Demo of Health Care Dataset

                         5k> Demo of Weather Dataset

  • Module 6: Live Project on Big Data & Hadoop

                         6a> Assessment

                         6b> Live Project

  • Module 7: Certification & Closure

                          7a> Certification of Completion

                         7b> Internship Certificate

                          7c> Review and Feedback

Sample Certification

  • Certificate of Completion