Course Overview

Big Data analytics is a multi step process that entails the systematic analysis of data and its underlying at every step of the process – commonly referred to as the “Big Data life cycle.” The Big Data life cycle is a derivative of the knowledge discovery in databases (KDD) process with subtle but important enhancements. Data mining and fusion has rapidly emerged as an enabling, robust, and scalable technique to analyze data for novel patterns, trends, anomalies, structures, and features that can be discovered from Big Data.

The course is divided into three main core topics:

Introduction to the Big Data problem. Current challenges, trends, and applications
Algorithms for Big Data analysis. Mining and learning algorithms that have been developed specifically to deal with large datasets
Technologies for Big Data management. Big Data technology and tools, special consideration made to the Map-Reduce paradigm and the Hadoop ecosystem.

at the end of this course, the student will become familiar with the fundamental concepts of Big Data management and analytics; will become competent in recognizing challenges faced by applications dealing with very large volumes of data as well as in proposing scalable solutions for them; and will be able to understand how Big Data impacts business intelligence, scientific discovery, and our day-to-day life.

Software Engineers, who are into ETL/Programming and exploring for great job opportunities in hadoop.
Managers, who are looking for the latest technologies to be implemented in their organization, to meet the current & upcoming challenges of data management.
Any Graduate/Post-Graduate, who is aspiring a great career towards the cutting edge technologies.

Java programming, Database basics

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