Hadoop & Data Science NLP (All in One Course).

Hadoop & Data Science NLP (All in One Course)., available at $19.99, has an average rating of 2.85, with 51 lectures, 6 quizzes, based on 14 reviews, and has 227 subscribers.

You will learn about You will be able to develop a real world an end to end application which will encompass both Hadoop as well as Natural Language Processing (Data Science). Setup a Hadoop Cluster on your laptop free of cost and then connect to different hadoop services. Develop distributed applications based on Hadoop Framework, Different Hadoop pillars, HDFS Architecture, MapReduce and different types of Data in Hadoop. Visualize Hadoop ecosystem services as well as components like Memory usage, Cluster Load etc. in the form of dashboard on a Web Interface called Ambari. Design and Develop scalable, fault tolerant and flexible applications which can store and distribute large data sets across inexpensive servers. Develop scripts based on several commands in Hadoop to manage files and datasets. Understand the different building blocks of Apache NIFI helping in data movement, transformation etc. Also learn about NIFI Architecture and its various applications. Steps to Install Apache NIFI and making changes in configuration files to run it seamlessly. Develop a complete workflow application in NIFI which can take data from the streaming source, perform transformations on this data and then store it in Hadoop. Spin up Apache Solr as one of the service, configure it to receive streaming data from NIFI processor to perform real time analytics on this data. Understand the architecture and concepts related to Apache Solr as well as several of its features. Create a Banana Dashboard to visualize the real time analytics happening on live streaming data after getting an understanding of components and structure of Banana Dashboard. Visualize where does Hive fit in Hadoop Ecosystem, its Architecture as well as how exactly it works. Develop an understanding of how data can be stored in structured form in Apache Hive. In depth knowledge of several of its components. Develop and Visualize the data in the form of Graphs, Histograms, Pie Charts etc. using another Hadoop Ecosystem tool (notebook) called Apache Zappelin. Develop the concepts of Natural Language Processing and integrate them all to develop a working NLP application. Develop basic building blocks of Natural Language Processing and write associated python scripts. Build a machine learning model using Python for the application going to be built. This course is ideal for individuals who are Anyone who wants to learn both Hadoop and Data Science from scratch. or Developers, Programmers or Database Administrators who want to transition to Hadoop and Hadoop Ecosystem tools like HDFS, Hive, Solr, NIFI, Banana and also wants to explore Data Science. or Aspiring Data Scientists, Data Analysts, Business Analysts who want to learn Natural Language Processing as an added arsenal as well as wants to learn Hadoop as well. or Product , Program or Project Managers who wants to understand the complete architecture as well as understand how Hadoop and Data Science can be integrated together. or Enterprise Architects, Solution Architects who wants to learn about Hadoop Ecosystem and related technologies to design Big Data related solutions. It is particularly useful for Anyone who wants to learn both Hadoop and Data Science from scratch. or Developers, Programmers or Database Administrators who want to transition to Hadoop and Hadoop Ecosystem tools like HDFS, Hive, Solr, NIFI, Banana and also wants to explore Data Science. or Aspiring Data Scientists, Data Analysts, Business Analysts who want to learn Natural Language Processing as an added arsenal as well as wants to learn Hadoop as well. or Product , Program or Project Managers who wants to understand the complete architecture as well as understand how Hadoop and Data Science can be integrated together. or Enterprise Architects, Solution Architects who wants to learn about Hadoop Ecosystem and related technologies to design Big Data related solutions.

Enroll now: Hadoop & Data Science NLP (All in One Course).

Summary

Title: Hadoop & Data Science NLP (All in One Course).

Price: $19.99

Average Rating: 2.85

Number of Lectures: 51

Number of Quizzes: 6

Number of Published Lectures: 51

Number of Published Quizzes: 6

Number of Curriculum Items: 58

Number of Published Curriculum Objects: 58

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

You will be able to develop a real world an end to end application which will encompass both Hadoop as well as Natural Language Processing (Data Science).
Setup a Hadoop Cluster on your laptop free of cost and then connect to different hadoop services.
Develop distributed applications based on Hadoop Framework, Different Hadoop pillars, HDFS Architecture, MapReduce and different types of Data in Hadoop.
Visualize Hadoop ecosystem services as well as components like Memory usage, Cluster Load etc. in the form of dashboard on a Web Interface called Ambari.
Design and Develop scalable, fault tolerant and flexible applications which can store and distribute large data sets across inexpensive servers.
Develop scripts based on several commands in Hadoop to manage files and datasets.
Understand the different building blocks of Apache NIFI helping in data movement, transformation etc. Also learn about NIFI Architecture and its various applications.
Steps to Install Apache NIFI and making changes in configuration files to run it seamlessly.
Develop a complete workflow application in NIFI which can take data from the streaming source, perform transformations on this data and then store it in Hadoop.
Spin up Apache Solr as one of the service, configure it to receive streaming data from NIFI processor to perform real time analytics on this data.
Understand the architecture and concepts related to Apache Solr as well as several of its features.
Create a Banana Dashboard to visualize the real time analytics happening on live streaming data after getting an understanding of components and structure of Banana Dashboard.
Visualize where does Hive fit in Hadoop Ecosystem, its Architecture as well as how exactly it works.
Develop an understanding of how data can be stored in structured form in Apache Hive. In depth knowledge of several of its components.
Develop and Visualize the data in the form of Graphs, Histograms, Pie Charts etc. using another Hadoop Ecosystem tool (notebook) called Apache Zappelin.
Develop the concepts of Natural Language Processing and integrate them all to develop a working NLP application.
Develop basic building blocks of Natural Language Processing and write associated python scripts.
Build a machine learning model using Python for the application going to be built.

Who Should Attend

Anyone who wants to learn both Hadoop and Data Science from scratch.
Developers, Programmers or Database Administrators who want to transition to Hadoop and Hadoop Ecosystem tools like HDFS, Hive, Solr, NIFI, Banana and also wants to explore Data Science.
Aspiring Data Scientists, Data Analysts, Business Analysts who want to learn Natural Language Processing as an added arsenal as well as wants to learn Hadoop as well.
Product , Program or Project Managers who wants to understand the complete architecture as well as understand how Hadoop and Data Science can be integrated together.
Enterprise Architects, Solution Architects who wants to learn about Hadoop Ecosystem and related technologies to design Big Data related solutions.

Target Audiences

Anyone who wants to learn both Hadoop and Data Science from scratch.
Developers, Programmers or Database Administrators who want to transition to Hadoop and Hadoop Ecosystem tools like HDFS, Hive, Solr, NIFI, Banana and also wants to explore Data Science.
Aspiring Data Scientists, Data Analysts, Business Analysts who want to learn Natural Language Processing as an added arsenal as well as wants to learn Hadoop as well.
Product , Program or Project Managers who wants to understand the complete architecture as well as understand how Hadoop and Data Science can be integrated together.
Enterprise Architects, Solution Architects who wants to learn about Hadoop Ecosystem and related technologies to design Big Data related solutions.

The demand for Big Data Hadoop Developers, Architects, Data Scientists, Machine Learning Engineers is increasing day by day and one of the main reason is that companies are more keen these days to get more accurate predictions & forecasting result using data. They want to make sense of data and wants to provide 360 view of customers thereby providing better customer experience.�

This course is designed in such a way that you will get an understanding of best of both worlds i.e. both Hadoop as well as Data Science. You will not only be able to perform Hadoop related operations to gather data from the source directly but also they can perform Data Science specific tasks and build model on the data collected. Also, you will be able to do transformations using Hadoop Ecosystem tools. So in a nutshell, this course will help the students to learn both Hadoop and Data Science Natural Language Processing in one course.�

Companies like Google, Amazon, Facebook, Ebay, LinkedIn, Twitter, and Yahoo! are using Hadoop on a larger scale these days and more and more companies have already started adopting these digital technologies. If we talk about Text Analytics, there are several applications of Text Analytics (given below) and hence companies prefer to have both of these skillset in the professionals.

One of the application of text classification is a faster emergency response system can be developed by classifying panic conversation on social media.
Another application is automating the classification of users into cohorts so that marketers can monitor and classify users based on how they are talking about products, services or brands online.
Content or product tagging using categories as a way to improve browsing experience or to identify related content on the website. Platforms such as news agencies, directories, E-commerce, blogs, content curators, and likes can use automated technologies to classify and tag content and products.

Companies these days are leaning towards candidates who are equipped with best of both worlds and this course will proved to be a very good starting point. This course covers complete pipeline of modern day ELT (Extract, Load and Transform) and Analytics as shown below:

Get data from Source –> Load data into Structured/Semi Structured/Unstructured form –> Perform Transformations �–> Pre-process the Data further –> Build the Data Science Model –> Visualize the Results

Learn and get started with the popular Hadoop Ecosystem technologies as well one the most of the most hot topics in Data Science called Natural Language Processing. In this course you will :

Do Hadoop Installation using Hortonworks Sandbox. You will also get an opportunity to do some hands-on with Hadoop operations as well as Hadoop Management Service called Amabrion your computer.
Perform HDFSoperations to work with continuous stream of data.
Install SSH and File Transfer related tools which helps in operational activities of Hadoop.
Perform NIFIinstallation and develop complete workflow on Web UI to move the data from source to destination. Also, perform transformations on this data using NIFI processors.
Spin up Apache Solr which allows full text search and also to receive text for performing Real Time Text Analysis.
Engage Banana Dashboard to visualize Real Time Analytics on streaming data.
Store the Real Time streaming JSON data in structured form using Hive Tables as well as in flat file format in HDFS.
Visualize the data in the form of Charts, Histograms using Apache Zappelin.
Learn the Building blocks of Natural Language Processing to develop Text Analytics Skills.
Unleash the Machine Learningcapabilities using Data Science Natural Language Processing and build a Machine Learning Model to classify Text Data.

Course Curriculum

Chapter 1: Introduction to Hadoop

Lecture 1: Course Introduction

Lecture 2: General Overview of Hadoop

Lecture 3: A quick look at Hadoop History

Lecture 4: Hadoop Framework and Ecosystem

Lecture 5: Let's learn about HDFS and Mapreduce

Lecture 6: Peak into Hadoop YARN

Chapter 2: Let's tame the Elephant – Install Hadoop Sandbox and Run few Hadoop commands

Lecture 1: Download Hadoop and other supporting tools on your Desktop/Laptop

Lecture 2: Install Hadoop and make Configuration changes.

Lecture 3: Access Hadoop Sandbox and Welcome Page.

Lecture 4: Let's do some hands-on with Hadoop Operations

Chapter 3: The Niagara Files – Introduction to Apache NIFI

Lecture 1: NIFI Concepts

Lecture 2: Acquire knowledge on Apache NIFI's UI Canvas Components

Lecture 3: Apache NIFI Architecture

Chapter 4: Install and Configure NIFI

Lecture 1: Download and Install Apache NIFI

Lecture 2: Configure Apache NIFI

Chapter 5: Full Text Search with Apache Solr – An Introduction

Lecture 1: An introduction of Apache Solr and some of its features

Lecture 2: Learn Basics and Components of Search Engine

Lecture 3: How Search Engine works ?

Lecture 4: Peak into the Architecture of Apache Solr

Lecture 5: Apache Solr – Basic Concepts

Chapter 6: Install and Configure Apache Solr

Lecture 1: Spin up Apache Solr and configure it to receive data.

Chapter 7: Twitter App Setup for bringing data into Hadoop

Lecture 1: Create Twitter App to get the tweets into Hadoop.

Chapter 8: Banana Dashboard for visualizing real time streaming data

Lecture 1: Introduction to Banana Dashboard – Overview, Components and Structure

Lecture 2: Spin up Banana Dashboard for Real Time Stream Analytics Visualization

Chapter 9: Apache Hive

Lecture 1: An Introduction to Apache Hive

Lecture 2: Apache Hive Architecture

Lecture 3: How does Apache Hive works ?

Lecture 4: Apache Hive Data Types

Lecture 5: Apache Hive – Create Database and Table

Lecture 6: Apache Hive – Table Partitioning

Lecture 7: Apache Hive – Operators and Functions

Lecture 8: Apache Hive – Views and Indexes

Lecture 9: Setup Hive Tables to receive JSON Format Data

Lecture 10: Create Hive Tables and Views for storing JSON Format Data

Lecture 11: Visualize Data using Apache Zappelin

Chapter 10: Data Science – Natural Language Processing

Lecture 1: NLP – Tokenizing Words and Sentences

Lecture 2: NLP – Word Stemming

Lecture 3: NLP – Get an understanding of Stopwords

Lecture 4: NLP – Dive into Part of Speech Tagging

Lecture 5: NLP – Locate and Classify entities using Named Entity Recognition

Lecture 6: NLP – Understand the concept of Lemmatization

Lecture 7: NLP – Build an Algorithmic classifier to classify the Text

Lecture 8: NLP – Importance of Words as Features

Lecture 9: NLP – Train a Machine Learning model using Naive Bayes Algorithm

Lecture 10: NLP – Get the Machine Learning model loaded faster using Pickling

Lecture 11: NLP – Putting everything together for Sentiment Analysis

Lecture 12: NLP – Real Time Live Twitter Sentiment Analysis

Lecture 13: NLP – Plotting Live Twitter Sentiments

Chapter 11: Free Bonus Material

Lecture 1: Free eBooks

Lecture 2: Free Apache Hive Book

Lecture 3: Free Natural Language Processing with Python eBook

Instructors

Nitin Kaushik
Hadoop, DataScience and Artificial Intelligence Evangelist

Rating Distribution

1 stars: 3 votes
2 stars: 1 votes
3 stars: 3 votes
4 stars: 2 votes
5 stars: 5 votes

Frequently Asked Questions

How long do I have access to the course materials?

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

Can I take my courses with me wherever I go?

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!

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