Projects in Hadoop and Big Data - Learn by Building Apps
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Projects in Hadoop and Big Data - Learn by Building Apps

A Practical Course to Learn Big Data Technologies While Developing Professional Projects
3.2 (112 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
3,680 students enrolled
Last updated 11/2015
English
English
Current price: $10 Original price: $50 Discount: 80% off
4 days left at this price!
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Includes:
  • 10 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand the Hadoop Ecosystem and Associated Technologies
  • Learn Concepts to Solve Real World Problems
  • Learn the Updated Changes in Hadoop
  • Use Code Examples Present Here to Create Your own Big Data Services
  • Get fully functional VMs fine tuned and created specifically for this course.
View Curriculum
Requirements
  • Working knowledge of Hadoop is expected before starting this course
  • Basic programming knowledge of Java and Python will be great
Description

The most awaited Big Data course on the planet is here. The course covers all the major big data technologies within the Hadoop ecosystem and weave them together in real life projects. So while doing the course you not only learn the nuances of the hadoop and its associated technologies but see how they solve real world problems and how they are being used by companies worldwide.

This course will help you take a quantum jump and will help you build Hadoop solutions that will solve real world problems. However we must warn you that this course is not for the faint hearted and will test your abilities and knowledge while help you build a cutting edge knowhow in the most happening technology space. The course focuses on the following topics

Add Value to Existing Data - Learn how technologies such as Mapreduce applies to Clustering problems. The project focus on removing duplicate or equivalent values from a very large data set with Mapreduce.

Hadoop Analytics and NoSQL - Parse a twitter stream with Python, extract keyword with apache pig and map to hdfs, pull from hdfs and push to mongodb with pig, visualise data with node js . Learn all this in this cool project.

Kafka Streaming with Yarn and Zookeeper - Set up a twitter stream with Python, set up a Kafka stream with java code for producers and consumers, package and deploy java code with apache samza.

Real-Time Stream Processing with Apache Kafka and Apache Storm - This project focus on twitter streaming but uses Kafka and apache storm and you will learn to use each of them effectively.

Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache Solr - Set up the relational schema for a Health Care Data dictionary used by the US Dept of Veterans Affairs, demonstrate underlying technology and conceptual framework. Demonstrate issues with certain join queries that fail on MySQL, map technology to a Hadoop/Hive stack with Scoop and HCatalog, show how this stack can perform the query successfully.

Log collection and analytics with the Hadoop Distributed File System using Apache Flume and Apache HCatalog - Use Apache Flume and Apache HCatalog to map real time log stream to hdfs and tail this file as Flume event stream. , Map data from hdfs to Python with Pig, use Python modules for analytic queries

Data Science with Hadoop Predictive Analytics - Create structured data with Mapreduce, Map data from hdfs to Python with Pig, run Python Machine Learning logistic regression, use Python modules for regression matrices and supervise training

Visual Analytics with Apache Spark on Yarn - Create structured data with Mapreduce, Map data from hdfs to Python with Spark, convert Spark dataframes and RDD’s to Python datastructures, Perform Python visualisations

Customer 360 degree view, Big Data Analytics for e-commerce - Demonstrate use of EComerce tool ‘Datameer’ to perform many fof the analytic queries from part 6,7 and 8. Perform queries in the context of Senitment analysis and Twiteer stream.

Putting it all together Big Data with Amazon Elastic Map Reduce - Rub clustering code on AWS Mapreduce cluster. Using AWS Java sdk spin up a Dedicated task cluster with the same attributes.


So after this course you can confidently built almost any system within the Hadoop family of technologies. This course comes with complete source code and fully operational Virtual machines which will help you build the projects quickly without wasting too much time on system setup. The course also comes with English captions. So buckle up and join us on our journey into the Big Data.

Who is the target audience?
  • Students who want to use Hadoop and Big Data in their Workplace and want to learn the implementation details for big data technologies.
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Curriculum For This Course
43 Lectures
10:11:43
+
Introduction
2 Lectures 03:32

Source VMs for the Projects

Virtual Machines for the Projects
13 pages
+
Add Value to Existing Data with Mapreduce
4 Lectures 57:45

Build and Run the Basic Code
14:08

Understanding the Code
13:54

Dependencies and packages
14:43
+
Hadoop Analytics and NoSQL
4 Lectures 55:15
Introduction to Hadoop Analytics
15:46

Introduction to NoSQL Database
15:28

Solution Architecture
14:50

Installing the Solution
09:11
+
Kafka Streaming with Yarn and Zookeeper
4 Lectures 01:00:43
Introduction to Kafka Yarn and Zookeeper
14:29

Code Structure
15:22

Creating Kafka Streams
15:17

Yarn Job with Samza
15:35
+
Real Time Stream processing with Apache Kafka and Apache Storm
4 Lectures 59:35
Real Time Streaming
15:09

Hortonbox Virtual Machine
14:58

Running in Cluster Mode
15:30

Submitting the Storm Jar
13:58
+
Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache S
4 Lectures 59:02
Introduction to the Project
14:14

Introduction to HDDAccess
14:46

Sqoop, Hive and Solr
13:56

Hive Usage
16:06
+
Log collection and analytics with the Hadoop Distributed File System using Apach
4 Lectures 58:36
Apache Flume and HCatalog
15:18

Install and Configure Apache Flume
14:51

Visualisation of the Data
14:51

Embedded Pig Scripts
13:36
+
Data Science with Hadoop Predictive Analytics
4 Lectures 59:59
Introduction to Data Science
14:48

Source Code Review
14:52

Setting Up the Machine
15:09

Project Review
15:10
+
Visual Analytics with Apache Spark on Yarn
4 Lectures 01:00:20
Project Setup
15:30

Setting Up Java Dependencies
15:24

Spark Analytics with PySpark
15:36

Bringing it all together
13:50
+
Customer 360 degree view, Big Data Analytics for e-commerce
4 Lectures 01:00:01
Ecommerce and Big Data
14:59

Installing Datameer
15:43

Analytics and Visualizations
15:50

Demonstration
13:29
2 More Sections
About the Instructor
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