Learn Hadoop, MapReduce and BigData from Scratch

A Complete Guide to Learn and Master the Popular Big Data Technologies

Learn Hadoop, MapReduce and BigData from Scratch

Price$199.00

SchoolUdemy
ScheduleOn Demand
LocationOnline
Duration17 hours
Credits0
Enroll
Rating
Reviews10
Popularity8941 Registered
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Difficultyall level
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Course DetailsCourse FAQ

Learn Hadoop, MapReduce and BigData from Scratch

Categories:
Software & IT

Modern companies estimate that only 12% of their accumulated data is analyzed, and IT professionals who are able to work with the remaining data are becoming increasingly valuable to companies. Big data talent requests are also up 40% in the past year.

Simply put, there is too much data and not enough professionals to manage and analyze it. This course aims to close the gap by covering MapReduce and its most popular implementation: Apache Hadoop. We will also cover Hadoop ecosystems and the practical concepts involved in handling very large data sets.

Learn and Master the Most Popular Big Data Technologies in this Comprehensive Course.

  • Apache Hadoop and MapReduce on Amazon EMR
  • Hadoop Distributed File System vs. Google File System
  • Data Types, Readers, Writers and Splitters
  • Data Mining and Filtering
  • Shell Comments and HDFS
  • Cloudera, Hortonworks and Apache Bigtop Virtual Machines

Mastering Big Data for IT Professionals World Wide
Broken down, Hadoop is an implementation of the MapReduce Algorithm and the MapReduce Algorithm is used in Big Data to scale computations. The MapReduce algorithms load a block of data into RAM, perform some calculations, load the next block, and then keep going until all of the data has been processed from unstructured data into structured data.

IT managers and Big Data professionals who know how to program in Java, are familiar with Linux, have access to an Amazon EMR account, and have Oracle Virtualbox or VMware working will be able to access the key lessons and concepts in this course and learn to write Hadoop jobs and MapReduce programs.

This course is perfect for any data-focused IT job that seeks to learn new ways to work with large amounts of data.

Contents and Overview
In over 16 hours of content including 74 lectures, this course covers necessary Big Data terminology and the use of Hadoop and MapReduce.

This course covers the importance of Big Data, how to setup Node Hadoop pseudo clusters, work with the architecture of clusters, run multi-node clusters on Amazons EMR, work with distributed file systems and operations including running Hadoop on HortonWorks Sandbox and Cloudera.

Students will also learn advanced Hadoop development, MapReduce concepts, using MapReduce with Hive and Pig, and know the Hadoop ecosystem among other important lessons.

Upon completion students will be literate in Big Data terminology, understand how Hadoop can be used to overcome challenging Big Data scenarios, be able to analyze and implement MapReduce workflow, and be able to use virtual machines for code and development testing and configuring jobs.

Course Details

Introduction to Big Data
online
chapter
On Demand
Introduction to the Course
online
lecture
<p style=""> Introduction to the Course </p>
On Demand
Why Hadoop, Big Data and Map Reduce Part - A
online
lecture
<p style=""> Introduction to Big Data, Hadoop and Map Reduce </p>
On Demand
Why Hadoop, Big Data and Map Reduce Part - B
online
lecture
On Demand
Why Hadoop, Big Data and Map Reduce Part - C
online
lecture
On Demand
Architecture of Clusters
online
lecture
<p> Lecture to help you understand the server cluster architecture </p>
On Demand
Virtual Machine (VM), Provisioning a VM with vagrant and puppet
online
lecture
<p style=""> Learn all about virtual machine provisioning </p>
On Demand
Hadoop Architecture
online
chapter
On Demand
Set up a single Node Hadoop pseudo cluster Part - A
online
lecture
<p style=""> Learn to setup the single node cluster </p>
On Demand
Set up a single Node Hadoop pseudo cluster Part - B
online
lecture
On Demand
Set up a single Node Hadoop pseudo cluster Part - c
online
lecture
On Demand
Clusters and Nodes, Hadoop Cluster Part - A
online
lecture
<p> Learn to set up a Hadoop Cluster </p>
On Demand
Clusters and Nodes, Hadoop Cluster Part - B
online
lecture
On Demand
NameNode, Secondary Name Node, Data Nodes Part - A
online
lecture
<p> Lecture about Node Hiearchy </p>
On Demand
NameNode, Secondary Name Node, Data Nodes Part - B
online
lecture
On Demand
Running Multi node clusters on Amazons EMR Part - A
online
lecture
<p> Learn to use Amazon web services for running multi node cluster </p>
On Demand
Running Multi node clusters on Amazons EMR Part - B
online
lecture
On Demand
Running Multi node clusters on Amazons EMR Part - C
online
lecture
On Demand
Running Multi node clusters on Amazons EMR Part - D
online
lecture
On Demand
Running Multi node clusters on Amazons EMR Part - E
online
lecture
On Demand
Distributed file systems
online
chapter
On Demand
Hdfs vs Gfs a comparison
online
lecture
<p> A comparison between HDFS and GFS file systems </p>
On Demand
Run hadoop on Cloudera, Web Administration
online
lecture
<p style=""> Learn to Run Hadoop on Cloudera </p>
On Demand
Run hadoop on Hortonworks Sandbox
online
lecture
<p style=""> Learn to run Hadoop on Hortonworks </p>
On Demand
File system operations with the HDFS shell Part - A
online
lecture
<p> Learn to perform file system operations using HDFS Shell </p>
On Demand
File system operations with the HDFS shell Part - B
online
lecture
On Demand
Advanced hadoop development with Apache Bigtop Part - A
online
lecture
<p> Learn all about Hadoop development using Apache Bigtop </p>
On Demand
Advanced hadoop development with Apache Bigtop Part - B
online
lecture
On Demand
Mapreduce Version 1
online
chapter
On Demand
MapReduce Concepts in detail Part - A
online
lecture
<p style=""> Learn the underlying concepts of the Map Reduce algorithm </p>
On Demand
MapReduce Concepts in detail Part - B
online
lecture
On Demand
Jobs definition, Job configuration, submission, execution and monitoring Part -A
online
lecture
<p> Learn to create Hadoop Jobs </p>
On Demand
Jobs definition, Job configuration, submission, execution and monitoring Part -B
online
lecture
On Demand
Jobs definition, Job configuration, submission, execution and monitoring Part -C
online
lecture
On Demand
Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part A
online
lecture
<p> Learn the basic syntax of Hadoop </p>
On Demand
Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part B
online
lecture
On Demand
Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part C
online
lecture
On Demand
The ETL class, Definition, Extract, Transform, and Load Part - A
online
lecture
<p> Learn all about the ETL class definition, transformation and load </p>
On Demand
The ETL class, Definition, Extract, Transform, and Load Part - B
online
lecture
On Demand
The UDF class, Definition, User Defined Functions Part - A
online
lecture
<p> Learn the basics of User defined class and functions </p>
On Demand
The UDF class, Definition, User Defined Functions Part - B
online
lecture
On Demand
Mapreduce with Hive ( Data warehousing )
online
chapter
On Demand
Schema design for a Data warehouse Part - A
online
lecture
<p style=""> Learn the schema design for data warehousing </p>
On Demand
Schema design for a Data warehouse Part - B
online
lecture
On Demand
Hive Configuration Part A
online
lecture
<p> Introduction to Hive and its use for Data Warehousing </p>
On Demand
Hive Configuration Part B
online
lecture
On Demand
Hive Query Patterns Part - A
online
lecture
<p> Learn all about Hive Query Patterns </p>
On Demand
Hive Query Patterns Part - B
online
lecture
On Demand
Hive Query Patterns Part - C
online
lecture
On Demand
Hive Query Patterns Part D
online
lecture
On Demand
Example Hive ETL class Part - A
online
lecture
<p> A live example to implement Hive ETL class </p>
On Demand
Example Hive ETL class Part - B
online
lecture
On Demand
Example Hive ETL class Part C
online
lecture
On Demand
Mapreduce with Pig (Parallel processing)
online
chapter
On Demand
Introduction to Apache Pig Part - A
online
lecture
<p style=""> Introduction to Parallel Processing using Apache Pig </p>
On Demand
Introduction to Apache Pig Part - B
online
lecture
On Demand
Introduction to Apache Pig Part - C
online
lecture
On Demand
Introduction to Apache Pig Part - D
online
lecture
On Demand
Pig LoadFunc and EvalFunc classes
online
lecture
<p style=""> Advance Pig features and usage of LoadFunc and EvalFunc Class </p>
On Demand
Example Pig ETL class Part - A
online
lecture
<p style=""> A working example of PIG ETL class </p>
On Demand
Example Pig ETL class Part - B
online
lecture
On Demand
The Hadoop Ecosystem
online
chapter
On Demand
Introduction to Crunch Part - A
online
lecture
<p style=""> A brief intro to Hadoop ecosystem and detail discussion on Crunch </p>
On Demand
Introduction to Crunch Part - B
online
lecture
On Demand
Introduction to Avro
online
lecture
<p style=""> Learn all about the Arvo hadoop component </p>
On Demand
Introduction to Mahout Part - A
online
lecture
<p style=""> Lecture discussing the use and implementation of Mahout </p>
On Demand
Introduction to Mahout Part - B
online
lecture
On Demand
Introduction to Mahout Part - C
online
lecture
On Demand
Mapreduce Version 2
online
chapter
On Demand
Apache Hadoop 2 and YARN Part - A
online
lecture
<p style=""> Introduction to Yarn and its usage in hadoop 2 </p>
On Demand
Apache Hadoop 2 and YARN Part - B
online
lecture
On Demand
Yarn Examples
online
lecture
<p style=""> Yarn Implementation examples for beginners. </p>
On Demand
Putting it all together
online
chapter
On Demand
Amazon EMR example Part - A
online
lecture
<p style=""> Implementing the concepts on Amazon web services. </p>
On Demand
Amazon EMR example Part - B
online
lecture
On Demand
Amazon EMR example Part - C
online
lecture
On Demand
Amazon EMR example Part - D
online
lecture
On Demand
Apache Bigtop example Part - A
online
lecture
<p style=""> A live example implementation of Apache Bigtop </p>
On Demand
Apache Bigtop example Part - B
online
lecture
On Demand
Apache Bigtop example Part - C
online
lecture
On Demand
Apache Bigtop example Part - D
online
lecture
On Demand
Apache Bigtop example Part - E
online
lecture
On Demand
Apache Bigtop example Part - F
online
lecture
On Demand
Course Summary
online
lecture
<p style=""> Course Summary </p>
On Demand
References
online
lecture
<p style=""> Reference links for various topics </p>
On Demand

FAQ

Q. How long do I have access to the course materials?

A. You can view and review the lecture materials indefinitely, like an on-demand channel.

Q. What is the refund policy on the course?

A. We like to keep our users happy, so we have a 30-day no questions asked refund policy. Send an email to [email protected] for refund requests.

Q. Can I take my courses with me wherever I go?

A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!


Reviews of Learn Hadoop, MapReduce and BigData from Scratch

  1. Posted by Swanand Bodas| March 16, 2016

    First slide speaker's voice was not clear. expected better slides. Slides are poorly written and with repeated text.

  2. Posted by Marshall Henderson| March 15, 2016

    This course using very old version of hadoop. I tried running with the latest version and had to many problems. I followed 1 page instructions on Apache web site and had hadoop up and running with in 1 hour using Hadoop version 2.6 on AWS EC2 instance. Also had allot of problems with vagrant where the version of vagrant I used did not match the coarse at all. I found my computer was not big enough to handle VM's. Probably would have been better to use AWS EC2 instances. I am at lesson 4 and still have no idea what MapReduce is for and how it works. Instructor repeats himself to much and comes across as very condescending.

  3. Posted by Sadman Khan| March 06, 2016

    really boring, and slow. but has has the right content

  4. Posted by Naveen Kumar Darsi| February 21, 2016

    Before jumping right into configurations, Little more theory wud have been gud. alas, it is gud :)

  5. Terrible. Simply Terrible
    Posted by Jay Kalavapudi| January 08, 2016

    With such an in-depth topic it helps to have structure and focus. This instructor is awful, repetitive, jumps around a lot, and spends time talking about things that aren't germane to learning how to work with Hadoop.

  6. Poor Communications
    Posted by Barry Ritter| December 09, 2015

    Instructors are quite dry and not clear and informative.

  7. Terrible Course
    Posted by Valentino Massimo| November 24, 2015

    Not instructive, Skips all over the place .. Don't waste your time or money on this course

  8. Outstanding
    Posted by Magdalena Scortea| November 23, 2015

    Excellent class Both instructors did an outstanding job in clarity and topic coverage.

  9. Informative Course
    Posted by Eshan Walia| October 29, 2015

    I found it that it very vast course on hadoop, got good knowledge while doing course. still i found it useful for me.

  10. Good-ish
    Posted by Oscar Barrios| August 06, 2015

    It seems that the whole course is given by a person that knows a lot about the subject but was somewhat improvised at the moment of explaining things. The outline is clear, but the material is a slapped bunch of "oh i forgot i have to give this course in a couple of hours" documents and the narration is the exact opposite of scripted. Add that to the fact that the tutor tries extremely hard to sound instructive but since he does not have a script ends up repeating the word "so" in a infomercial tone about 10 times per sentence and you'll end up screaming for him to stop saying anything. As said, the instructor knows the subject but the material is poor, and is very obvious that is improvised.

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