CIS 468 - Big Data

[3 credit(s)]

The course introduces fundamental concepts to design and implement an intelligent system (AI) as a big data processing and analytic application. The course provides design strategies and methodologies to build a big data application as an intelligent web application that processes machine generated big data for data analytic processing with information retrieval and machine learning algorithms. It explores a number of related subjects - common characteristics of machine generated big data formats from social network sites or any web servers, big data as a semi structured data model or unstructured data and data processing techniques, big data processing systems with semi structured data model, semi structured database systems with modeling and design of semi-structured databases, and manipulation and retrieval methods as a backend system of an intelligent system for a big data processing. The course also introduces topics related to distributed data processing systems for performance optimization strategies of big data processing with parallel data processing systems and parallel programming paradigms Map Reduce in Hadoop Distributed File System (HDFS). The course also introduces topics on basic methods and algorithms for big data analytics and unstructured text analytics from related CS disciplines: Machine Learning, Information Retrieval, and Natural Language Processing (NLP). Furthermore, the course introduces new platforms and architectures of big data processing systems with hand on experience on Cloud based parallel data processing systems.

Semesters Offered: Every Spring

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