Big Data and Hadoop for Absolute Beginners

Big Data and Hadoop for Absolute Beginners, available at $54.99, has an average rating of 4.45, with 51 lectures, based on 489 reviews, and has 6838 subscribers.

You will learn about You would learn how to install and build up a Hadoop Cluster from scratch. You would understand all the key concepts associated with Big Data and Hadoop and their purpose. You would become proficient in administering or managing the Hadoop Cluster. You would also learn all the concepts related to programming in MapReduce. You would learn how to write programs using MapReduce. This course is ideal for individuals who are Basic knowledge of Unix / Linux required for becoming a Hadoop Admin. or Basic programming knowledge required for becoming a Hadoop Developer. or Knowledge of Core Java would be desirable for a Hadoop Developer. It is particularly useful for Basic knowledge of Unix / Linux required for becoming a Hadoop Admin. or Basic programming knowledge required for becoming a Hadoop Developer. or Knowledge of Core Java would be desirable for a Hadoop Developer.

Enroll now: Big Data and Hadoop for Absolute Beginners

Summary

Title: Big Data and Hadoop for Absolute Beginners

Price: $54.99

Average Rating: 4.45

Number of Lectures: 51

Number of Published Lectures: 51

Number of Curriculum Items: 51

Number of Published Curriculum Objects: 51

Original Price: $84.99

Quality Status: approved

Status: Live

What You Will Learn

You would learn how to install and build up a Hadoop Cluster from scratch.
You would understand all the key concepts associated with Big Data and Hadoop and their purpose.
You would become proficient in administering or managing the Hadoop Cluster.
You would also learn all the concepts related to programming in MapReduce.
You would learn how to write programs using MapReduce.

Who Should Attend

Basic knowledge of Unix / Linux required for becoming a Hadoop Admin.
Basic programming knowledge required for becoming a Hadoop Developer.
Knowledge of Core Java would be desirable for a Hadoop Developer.

Target Audiences

Basic knowledge of Unix / Linux required for becoming a Hadoop Admin.
Basic programming knowledge required for becoming a Hadoop Developer.
Knowledge of Core Java would be desirable for a Hadoop Developer.

Do you find Big Data and Hadoop confusing? Aspire to become a Big Data or Hadoop professional? But not sure which course to enroll? Then this course is for you !

OVER 5000+ SUCCESSFUL STUDENTS HAVE ALREADY TAKEN THIS COURSE. 100% Satisfaction Guaranteed |RISK FREE INVESTMENT – 30 DAYS NO QUESTIONS ASKED MONEY BACK GUARANTEE. Course Overview:

Most demanding and sought after skill of the decade.
Secure your career by learning Big Data and Hadoop.
Course taught using a very innovative and simplified method of teaching.
Course covers all the topics related to Hadoop Adminsitration as well as Hadoop Development.

Course Description: In this course, you would be learning all the concepts and terminologies related to Big Data and Hadoop, such as the NameNode, Secondary NameNode, DataNode, JobTracker and TaskTracker, along with other concepts related to it such as what is meant by Rack Awareness and NameNode Federation in a simplified way. It also explains how the data is managed by the Hadoop Distributed File System (HDFS) and explains the process of reading and writing data onto the Hadoop Distributed File System. Later in the course you would also learn how to add or remove a DataNode or a TaskTracker to an existing cluster, how to check the HDFS for errors, Balancing the DataNode and so on. You would also learn all the concepts related to programming in MapReduce along with writing programs using MapReduce. Upon completion of this course, you would have a clear idea about, all the concepts related to the Hadoop, that should be sufficient to help you start off with Administering the Hadoop Cluster as well as Developing MapReduce Applications for Hadoop Cluster. All the Best and Happy Learning !

Course Curriculum

Chapter 1: Introduction to Big Data and Hadoop

Lecture 1: What is Big Data?

Lecture 2: Classification of Big Data.

Lecture 3: Characteristics of Big Data.

Lecture 4: Challenges Associated with Big Data.

Lecture 5: Traditional Approach of Storing and Processing Big Data.

Lecture 6: What is Hadoop?

Lecture 7: Features of Hadoop.

Lecture 8: How Hadoop Works?

Lecture 9: What is Hadoop EcoSystem?

Chapter 2: Exploring HDFS

Lecture 1: What is HDFS?

Lecture 2: HDFS Daemons: NameNode and DataNode Explained.

Lecture 3: HDFS Daemons: Secondary NameNode Explained.

Lecture 4: How HDFS Manages FileSystem MetaData?

Lecture 5: Reading Data from HDFS.

Lecture 6: Writing Data to HDFS.

Lecture 7: What is Rack Awareness?

Lecture 8: NameNode Federation Explained.

Chapter 3: Exploring MapReduce

Lecture 1: What is MapReduce?

Lecture 2: MapReduce Daemons JobTracker and TaskTracker Explained.

Lecture 3: What is YARN?

Chapter 4: Understanding MapReduce Programming Framework

Lecture 1: How MapReduce Works?

Lecture 2: What is Key / Value Pair?

Lecture 3: Hadoop Java API’s Explained.

Chapter 5: Installing a Single Node, Pseudo Hadoop Cluster on a Local Machine

Lecture 1: Understanding Hadoop Operating Modes.

Lecture 2: Creating a Virtual Machine in VMWare.

Lecture 3: Downloading Linux.

Lecture 4: Installing Linux.

Lecture 5: Configuring Linux.

Lecture 6: Downloading and Installing Hadoop.

Lecture 7: Configuring Hadoop and Starting Up the Hadoop Cluster.

Chapter 6: Installing a Multi Node, Fully Distributed, Hadoop Cluster on a Local Machine

Lecture 1: Setting up a MultiNode Apache Hadoop Cluster on Local Machine Part 1

Lecture 2: Setting up a MultiNode Apache Hadoop Cluster on Local Machine Part 2

Lecture 3: Setting up a MultiNode Apache Hadoop Cluster on Local Machine Part 3

Lecture 4: Setting up a MultiNode Apache Hadoop Cluster on Local Machine Part 4

Chapter 7: Amazon EC2 Basics

Lecture 1: Setting Up and Connecting to an Amazon EC2 Instance.

Chapter 8: Maintaining a Hadoop Cluster

Lecture 1: Finding Data for Practice.

Lecture 2: Starting and Stopping Hadoop Daemons.

Lecture 3: Adding a Node to the Cluster.

Lecture 4: Removing a Node from the Cluster.

Lecture 5: Checking the Hadoop Distributed File System.

Lecture 6: Exploring Commands in Hadoop.

Lecture 7: Adding a TaskTracker.

Lecture 8: Removing a TaskTracker.

Lecture 9: Importing Data into HDFS.

Lecture 10: Exporting Data out of HDFS.

Lecture 11: Copying Data Using DistCP.

Lecture 12: Balancing a DataNode.

Lecture 13: Turning On & Turning Off SafeMode.

Lecture 14: Hadoop Commands Reference Guide.

Chapter 9: Programming with MapReduce

Lecture 1: Setting Up Development Environment.

Lecture 2: More to Follow.

Instructors

IT Skills In Demand
Demanding Skills Thought in a Simplified Way.

Rating Distribution

1 stars: 24 votes
2 stars: 28 votes
3 stars: 85 votes
4 stars: 167 votes
5 stars: 185 votes

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