Taught by a 4 person team including 2 Stanford–educated, ex–Googlers and 2 ex–Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data.
This course is a zoom–in, zoom–out, hands–on workout involving Hadoop, MapReduce and the art of thinking parallel.
Let s parse that.
Zoom–in, Zoom–Out: This course is both broad and deep. It covers the individual components of Hadoop in great detail, and also gives you a higher level picture of how they interact with each other.
Hands–on workout involving Hadoop, MapReduce : This course will get you hands–on with Hadoop very early on. You’ll learn how to set up your own cluster using both VMs and the Cloud. All the major features of MapReduce are covered – including advanced topics like Total Sort and Secondary Sort.
The art of thinking parallel: MapReduce completely changed the way people thought about processing Big Data. Breaking down any problem into parallelizable units is an art. The examples in this course will train you to hink parallel .
Lot’s of cool stuff ..
.. and of course all the basics:
Courses : 23
Specification: Learn By Example: Hadoop, MapReduce for Big Data problems
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