Big Data Science with Apache Hadoop, Pig and Mahout

Learn to execute Big Data Science Projects and deliver results using Apache Hadoop, MapReduce, Pig, Hive and Mahout
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  • Lectures 52
  • Length 9.5 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 5/2015 English

Course Description

"Data Science is the sexiest job of the 21st century - It has exciting work and incredible pay".

Learning Data Science though is not an easy task. The field traverses through Computer Science, Programming, Information Theory, Statistics and Artificial Intelligence. College/University courses in this field are expensive. Becoming a Data Scientist through self-study is challenging since it requires going through multiple books, websites, searches and exercises and you will still end up feeling "not complete" at the end of it. So how do you acquire full-stack Data Science skills that will get you a and give you the confidence to execute it?

Big Data Science with Hadoop addresses the problem. This course provides extensive, end-to-end coverage of all activities performed in a Data Science project. If teaches application of the latest techniques in data acquisition, transformation and predictive analytics to solve real world business problems. The goal of this course is to teach practice rather than theory. Rather than deep dive into formula and derivations, it focuses on using existing libraries and tools to produce solutions. It also keeps things simple and easy to understand.

Through this course, we strive to make you fully equipped to become a developer who can execute full fledged Data Science projects. By taking this course, you will

  • Appreciate what Data Science really is
  • Understand the Data Science Life Cycle
  • Learn Apache Hadoop, Map Reduce, Pig, Mahout and Hive.
  • Apply Hadoop technologies for executing Data Science Projects
  • Master the application of Analytics and Machine Learning techniques
Big Data and Data Science go hand in hand and this is a great course to learn both !!

Please note: This course only covers Hadoop components as-required for Data Science. It does not provide exhaustive coverage.

What are the requirements?

  • Linux experience
  • Java Programming experience preferred
  • SQL experience preferred

What am I going to get from this course?

  • Appreciate what Data Science really is
  • Understand the Data Science Life Cycle
  • Learn to use Apache Hadoop, Map Reduce, Pig and Mahout for executing Data Science projects
  • Master the application of Analytics and Machine Learning techniques

What is the target audience?

  • IT Professionals aspiring to be Data Scientists
  • Students who want to learn about Data Science domain
  • Statisticians and Project Managers who want to expand their horizon into Data Science

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Introduction
About the Course
Preview
10:43
About V2 Maestros
Preview
02:07
Resource Bundle
Article
Section 2: What is Data Science?
Basic Elements of Data Science
11:51
The Dataset
10:44
Learning from Relationships
Preview
12:55
Modeling and Predictions
09:31
Use Cases for Data Science
07:47
Section 3: Data Science Life Cycle
Stage 1 - Setup
11:46
Stage 2 - Data Engineering
11:57
Stage 3 - Analysis and Production
19:16
Section 4: Statistics for Data Science
Types of Data
07:29
Summary Statistics
16:10
Statistical Distributions
Preview
19:05
Correlations
10:09
Section 5: Data Engineering
Data Acquisition
16:01
Data Cleansing
10:50
Data Transformations
11:09
Text Processing - TF-IDF
14:53
Section 6: Apache Hadoop
Hadoop Overview
10:06
Setting up the Cloudera VM
06:51
About HDFS
14:46
HDFS Usage Examples
06:01
Introduction to Map Reduce
17:24
A Map Reduce example in Java
16:46
The Hadoop Stack
Preview
06:27
Hadoop tools for Data Science
03:34
Section 7: Apache Sqoop and Hive
Sqoop Overview and examples
07:32
Hive Overview
14:18
Hive Examples
06:10
Section 8: Apache Pig
Apache Pig Overview
08:31
Pig Latin Basics
10:25
Pig Latin Operations
15:29
Data Engineering with Pig
07:55
Examples - Pig Latin Operations
14:57
Examples - Data Engineering with Pig
12:15
Section 9: Machine Learning with Apache Mahout
Types of Analytics
12:08
Types of Learning
17:16
Analyzing results and errors
13:46
Apache Mahout Overview
03:30
Decision Trees
10:42
Random Forests
10:31
Mahout example - Random Forests
14:40
Naive Bayes Classifier
19:21
Mahout example - Naive Bayes
11:14
K Means Clustering
11:53
Mahout example - K Means Clustering
10:17
Recommendation Systems
11:55
Mahout example - User Based Recommender
10:48
Section 10: Case Studies
Use Case : Predicting Heart Disease
15:56
Section 11: Conclusion
Closing Remarks
02:01
BONUS Lecture : Other courses you should check out
Article

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Instructor Biography

V2 Maestros, Big Data Science / Analytics Experts | 10K+ students

V2 Maestros is dedicated to teaching big data / data science at affordable costs to the world. Our instructors have real world experience practicing big data and data science and delivering business results. Big Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building data science talent across the world.

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