A student must fulfill the course prerequisites as listed in the catalog description: CIS 3260 or CSc 2310; CSP 1-8. Prerequisites are strictly enforced.

• Required Text: V. Dhar and R. Stein, Intelligent Decision Support Methods : The Science of Knowledge Work, Prentice Hall, 1997.
• Reference Text: Data Mining Techniques, Michael Bery and Gordon Linoff (BL), Wiley 1997 (in Library Reserve).
• Class handouts / overheads
• Software tools to be discussed in class

1. Barr, D. and Mani, G.: Using Neural Nets to Manage Investments, AI Expert, February 1994.
2. Stein, R., "Selecting and Preprocessing Data for Neural Networks," AI Expert February and March, 1993.

This course provides an introduction to the fundamentals of Intelligent Systems. Businesses are becoming increasingly "knowledge intensive". In particular, with the explosion in the amount of data available, there is an increasing need for systems that help people filter, summarize, and interpret large amounts of very disparate kinds of data. At the same time, the enabling technologies such as database systems, networks, desktops, and Artificial Intelligence techniques have reached industrial strength maturity, providing unprecedented opportunities for building powerful decision support systems.

Whether you are an information systems professional or a business manager/user, you need to understand the value the new technologies provide and how to recognize when they are useful. This course will give you a broad understanding of these technologies, a methodology that lets you evaluate the pros and cons of each of the technologies in the context of real-world problems, and exposure to business cases where this methodology has been applied.

• Understand different uses of intelligent systems in various business domains
• Understand the steps involved in developing an intelliegent system
• Acquire working knowledge of several popular knowledge based techniques
• Apply the various techniques to solve business problems
• Acquire a working knowledge of some popular tools for knowledge systems design
• Learn to recognize and overcome the obstacles in knowledge systems development and use
• Become aware of the emerging tools and techniques to support knowledge systems.
• Create commonly expected "deliverables" of a knowledge systems project in a group project.

This course has ambitious objectives and will be only as beneficial to you as you want to make it for yourself. Expect to spend some time on the often-steep learning curve of the some intelligent systems / tools. Broad knowledge about the various aspects of intelligent systems from business, technical and end user perspectives gained in class will be applied in a team project and case analyses. Classes will consist of a combination of lectures, discussions of business cases, and software demonstrations. Experts from the industry will make occasional presentations.