500

INDS 555 Introduction of Databases for Data Science

This course is designed to introduce graduate students to the foundations of database systems, focusing on relational algebra and data model, query optimization and query processing. Students would also be introduced to practical database design and implementation including SQL and NoSQL programming. Other topics to be covered include Data and Database Security, Object-Relational Databases, Database Tuning, Transaction processing, Concurrency control , Database recovery techniques, Electronic commerce, Distributed Databases.

3

INDS 573 Big Data and Distributed Database Systems Management

This course is designed to introduce graduate students to the large data warehousing, "Cloud" computing, Hadoop and similar distributed/parallel systems. Students would also be introduced to the current data mining tools. The students will learn about the general architecture of data mining systems, techniques and algorithms of practical utility, types of patterns that can be found in practically important systems. Data mining primitives and query languages, an integration of a data mining system with databases and data warehouses will be investigated; essential insights in data mining systems of the future will be given. Students are also expected to be able to clearly communicate the data mining results.

3

INDS 589 Special Topics

Topics of special or current interest offered periodically and taught from an interdisciplinary perspective.

1-4

INDS 590 Independent Study

Independent study of interdisciplinary topics not covered in regular graduate course offerings and pertinent to the student's program of study.

1-3