Information and Knowledge Management
ISBT 311: BIOINFORMATICS
This course examines current biological problems and explore and develop bioinformatic solutions to these issues. Each topic includes a definition of the problem, a review of the basic biological concepts involved, an introduction to the computational techniques used to address the problem along with a utilization of existing web-based tools and software solutions often employed by professionals in the field of bioinformatics. Biological topics include those such as antibiotic resistance, genetic disease, and genome sequencing. Computational solutions will use industry-standard tools including the Perl and LabVIEW algorithm development languages.
ISBT 312: COLLABORATIVE SOFTWARE DEVELOPMENT
This course will introduce students to the tenets of collaborative software development. As the majority of commercial and professional software is developed by a group of software engineers rather than individuals, this course will examine methods of software project management and specifically utilize the agile development method of Extreme Programming. Working software will be developed throughout the course. The initial project will use National Instruments LabVIEW. The second project will introduce the text-based, ANSI C language, National Instruments LabWindows/CVI. The final project will use the Microsoft Visual Studio.NET development platform. Prerequisite: ISBT 311
ISBT 411: INTELLIGENT SYSTEMS
This course presents a systematic introduction to the fundamentals of computational intelligence, including in-depth examination of artificial neural networks, evolutionary computing, swarm intelligence and fuzzy systems. Computational intelligence is the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments. Specific environments examined will include Laboratory Automation, Automated Process Control, Robotics, and Business Decision Support.
ISBT 412: KNOWLEDGE DISCOVERY
This course will introduce students to the Knowledge Discovery process with special concentration on the various concepts and algorithms of Data Mining. Specific topics include an examination of Online Analytical Processing (OLAP), data warehousing, information retrieval, and machine learning. The core concepts of classification, clustering, association rules, prediction, regression, and pattern matching are followed by a discussion of advanced topics such as mining temporal data, spatial data, and Web mining. This course will incorporate the algorithms examined in ISBT 411—Intelligent Systems—and will emphasize the importance of Knowledge Discovery and Data Mining in research, product development, and production facilities. Prerequisite: ISBT 411