Courses

Data and database management and advanced SQL techniques; issues of data security, backup and recovery, large scale databases, master data management, concurrent user data access, scalability, and policies.

This course provides an introduction to the concepts and technologies of big data. Key concepts and techniques allow organizations to analyze structured and unstructured data/information collected from transaction processing systems, data warehouses, and distributed systems. The ultimate purpose of descriptive, predictive, and prescriptive analytics is to support high quality decision support for executives and managers.

The focus here is on the management of data and the technologies which specifically targets mass data storage with a view to online and after-the-fact examination of data to acquire new insights. The major topics include: data warehouse planning, data warehouse models, and supporting software, date mining concepts and tools, creation of data mining models for the tools and matching the tool to the task.

This course delves into advanced techniques and methodologies for extracting knowledge and meaningful insights from large and complex data sources. It covers data mining methodologies, including measurement, evaluation, and visualization, alongside advanced algorithms and applications. Students will learn to address real-world challenges across diverse domains such as business, healthcare, finance, and social networks.

This course provides in-depth coverage of advanced data mining and information retrieval principles and techniques. It also offers extensive training and practice opportunities in frontier research directions.

The first part of the course covers how to build a cloud infrastructure based on a cloud computing reference model. The second part of the course cover backup and recovery infrastructure.

Advanced concepts, technologies, and methodologies used to electronically store and manage data using Storage Area Network, Network Attached Storage, and other technologies. The structure of the course combines lecture and labs. Credit is not given this course and INFO 4150. Prerequisite INFO 6140 or INFO 4100.

In-depth review and application of current debriefing models in the field of simulation. Emphasis on choosing effective debriefing models for various modalities of simulation.

This course will examine the process of data preparation, mining methods, and how to mine data using current programming tools. Topics include data selection, cleaning, coding, using different data mining and machine learning techniques, and visualization of the generated structures. Students will develop hands on experience developing supervised and unsupervised data mining algorithms and will learn how to employ these techniques in context of various business applications.

An advanced study of dental assisting expanded functions with emphasis on four-handed dentistry utilization of tray setups for specific general practice and specialty procedures. A grade of C or better is required in this course to take the next course.