Projects in Hadoop and Big Data Learn by Building Apps

Projects in Hadoop and Big Data – Learn by Building Apps, available at $19.99, has an average rating of 3.05, with 44 lectures, based on 157 reviews, and has 4130 subscribers.

You will learn about 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. This course is ideal for individuals who are Students who want to use Hadoop and Big Data in their Workplace and want to learn the implementation details for big data technologies. It is particularly useful for Students who want to use Hadoop and Big Data in their Workplace and want to learn the implementation details for big data technologies.

Enroll now: Projects in Hadoop and Big Data – Learn by Building Apps

Summary

Title: Projects in Hadoop and Big Data – Learn by Building Apps

Price: $19.99

Average Rating: 3.05

Number of Lectures: 44

Number of Published Lectures: 44

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will 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.

Who Should Attend

Students who want to use Hadoop and Big Data in their Workplace and want to learn the implementation details for big data technologies.

Target Audiences

Students who want to use Hadoop and Big Data in their Workplace and want to learn the implementation details for big data technologies.

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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Virtual Machines for the Projects

Chapter 2: Add Value to Existing Data with Mapreduce

Lecture 1: Introduction to the Project

Lecture 2: Build and Run the Basic Code

Lecture 3: Understanding the Code

Lecture 4: Dependencies and packages

Chapter 3: Hadoop Analytics and NoSQL

Lecture 1: Introduction to Hadoop Analytics

Lecture 2: Introduction to NoSQL Database

Lecture 3: Solution Architecture

Lecture 4: Installing the Solution

Chapter 4: Kafka Streaming with Yarn and Zookeeper

Lecture 1: Introduction to Kafka Yarn and Zookeeper

Lecture 2: Code Structure

Lecture 3: Creating Kafka Streams

Lecture 4: Yarn Job with Samza

Chapter 5: Real Time Stream processing with Apache Kafka and Apache Storm

Lecture 1: Real Time Streaming

Lecture 2: Hortonbox Virtual Machine

Lecture 3: Running in Cluster Mode

Lecture 4: Submitting the Storm Jar

Chapter 6: Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache S

Lecture 1: Introduction to the Project

Lecture 2: Introduction to HDDAccess

Lecture 3: Sqoop, Hive and Solr

Lecture 4: Hive Usage

Chapter 7: Log collection and analytics with the Hadoop Distributed File System using Apach

Lecture 1: Apache Flume and HCatalog

Lecture 2: Install and Configure Apache Flume

Lecture 3: Visualisation of the Data

Lecture 4: Embedded Pig Scripts

Chapter 8: Data Science with Hadoop Predictive Analytics

Lecture 1: Introduction to Data Science

Lecture 2: Source Code Review

Lecture 3: Setting Up the Machine

Lecture 4: Project Review

Chapter 9: Visual Analytics with Apache Spark on Yarn

Lecture 1: Project Setup

Lecture 2: Setting Up Java Dependencies

Lecture 3: Spark Analytics with PySpark

Lecture 4: Bringing it all together

Chapter 10: Customer 360 degree view, Big Data Analytics for e-commerce

Lecture 1: Ecommerce and Big Data

Lecture 2: Installing Datameer

Lecture 3: Analytics and Visualizations

Lecture 4: Demonstration

Chapter 11: Putting it all together Big Data with Amazon Elastic Map Reduce

Lecture 1: Introduction to the Project

Lecture 2: Configuration

Lecture 3: Setting Up Cluster on EMR

Lecture 4: Dedicated Task Cluster on EMR

Chapter 12: Summary

Lecture 1: Summary

Lecture 2: Bonus Lecture: More Interesting Stuff, Offers and Discounts

Instructors

Eduonix Learning Solutions
1+ Million Students Worldwide | 200+ Courses

Eduonix-Tech .

Eduonix Support

Rating Distribution

1 stars: 22 votes

2 stars: 16 votes

3 stars: 30 votes

4 stars: 41 votes

5 stars: 48 votes

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