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"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
Please note: This course only covers Hadoop components as-required for Data Science. It does not provide exhaustive coverage.
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|Section 1: Introduction|
About the CoursePreview
About V2 MaestrosPreview
|Section 2: What is Data Science?|
Basic Elements of Data Science
Learning from RelationshipsPreview
Modeling and Predictions
Use Cases for Data Science
|Section 3: Data Science Life Cycle|
Stage 1 - Setup
Stage 2 - Data Engineering
Stage 3 - Analysis and Production
|Section 4: Statistics for Data Science|
Types of Data
|Section 5: Data Engineering|
Text Processing - TF-IDF
|Section 6: Apache Hadoop|
Setting up the Cloudera VM
HDFS Usage Examples
Introduction to Map Reduce
A Map Reduce example in Java
The Hadoop StackPreview
Hadoop tools for Data Science
|Section 7: Apache Sqoop and Hive|
Sqoop Overview and examples
|Section 8: Apache Pig|
Apache Pig Overview
Pig Latin Basics
Pig Latin Operations
Data Engineering with Pig
Examples - Pig Latin Operations
Examples - Data Engineering with Pig
|Section 9: Machine Learning with Apache Mahout|
Types of Analytics
Types of Learning
Analyzing results and errors
Apache Mahout Overview
Mahout example - Random Forests
Naive Bayes Classifier
Mahout example - Naive Bayes
K Means Clustering
Mahout example - K Means Clustering
Mahout example - User Based Recommender
|Section 10: Case Studies|
Use Case : Predicting Heart Disease
|Section 11: Conclusion|
BONUS Lecture : Other courses you should check out
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.