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Hadoop is a hot new technology that is growing everyday in its adaption in the Big Data world. However, Hadoop is built using Java and application developers need to know/learn Java for developing MapReduce applications. Python is a very popular programming language that makes the development of applications simple and easy. Hadoop provides a way by which MapReduce applications can be built using Python. This way, developers can use existing knowledge and code base for quickly developing MapReduce applications.
This intent of this course is to help Python developers learn the concepts and techniques for developing real world applications in Hadoop. It walks the learner through 5 examples of increasing difficulty for mastering MapReduce through Python.
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|Section 1: Introduction|
Introduction to the coursePreview
About V2 MaestrosPreview
Set of files and datasets used in examples for this course
|Section 2: Hadoop Basics|
Setting up the Cloudera VM
HDFS Usage Examples
Introduction to Map Reduce
A Map Reduce example in Java
The Hadoop Stack
|Section 3: Python with Hadoop|
Introduction to Hadoop Streaming
Using Python with Hadoop Streaming
|Section 4: Hadoop - Python Use Cases|
Use Case 1 : Basic Data Cleansing
Use Case 2 : Data Filtering
Use Case 3 : Data Summarization
Use Case 4 : Joining Data
Introduction to Text Processing / TF-IDF
Use Case 5 : Computing TF-IDF
|Section 5: 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.