KSE521: Business Intelligence

Organizations are heavily dependent on computerized support in collecting data from their operations and converting them into information for decision making. Effective decisions can be made only when people have the right information. Business intelligence plays a pivotal role in transforming a large set of data into information for effective decision making. The ability to understand, digest, analyze, and filter information is essential to success for any professional in any industry. Therefore, the overall goal of this course is to cover the fundamental concepts and skills associated with major business intelligence applications including database, data warehouse, data mining, OLAP, and business intelligence reporting. Toward achieving this goal, the course uses a combination of lectures, discussions, hands-on exercises, and assignments.

Learning objectives for this course include:

   • To understand the fundamental concepts of database, data warehouse, data mining, and business intelligence.
   • To learn how to properly fit a model to the data and evaluate its performance from the business perspective.
   • To learn key modeling and visualization techniques using a popular analytical tool (i.e. R, Python).
   • To understand the fundamental concepts of database and SQL to issue meaningful ad-hoc queries for management purposes.

You can download the lecture notes and other class materials from the following link:

•    • KSE521 Course Website

KSE612: Human Decision Making and Support

Life is full of choices. We make decisions every day and those decisions determine the story of our life and the legacy we leave behind. Decision making is central to the survival and advancement of human race and to the function and success of knowledge workers. Understanding how people make decisions has also immense implications for the effective design and successful implementation of computerized tools and systems. The primary focus of this course is on understanding how people make decisions and how decision making could be improved. Various types, strategies, limitations, and models of human decision making are considered. Human problem solving strategies and heuristics in choice, estimation, and diagnosis problems are analyzed. Also discussed are various intelligent approaches and systems to support the human strategies by providing timely and well-designed information.

By the end of this course you should be able to:

   • Demonstrate deep understanding of the psychological processes involved in judgment and decision making and understand when and why those processes lead to
     (more or less) accurate or inaccurate judgments.
   • Compare and contrast different theories that explain how people perceive, attend to, and process information to make judgments and decisions.
   • Apply the concepts, theories, models learned from the course to the design of academic research to produce an experimental research paper on judgment and decision making.

You can download the lecture notes and other class materials from the following link:

•    • KSE612 Course Website

KSE643: Knowledge Engineering and Intelligent Decision Making

Knowledge constitutes an integral part of intelligent decision making. People make various decisions about what to do based on what they know. Knowledge engineering plays a key role in integrating human knowledge into computer systems for intelligent decision making. This course covers the fundamental concepts, methods, techniques, and tools related to knowledge engineering, and applies them to the Web for the design of intelligent decision making systems.

Learning objectives for this course include:

   • To understand the fundamental concepts of knowledge engineering.
   • To learn various methods, techniques, and tools related to building recommender systems.
   • To develop essential skills necessary for the design of intelligent decision making systems (e.g., recommender systems, knowledge-based systems).
   • To be aware of key issues surrounding knowledge engineering and recommender systems.

You can download the lecture notes and other class materials from the following link:

•    • KSE643 Course Website

KSE966/986: Seminar in MS/Ph.D

The department regularly offers seminars on up-to-date topics to help M.S. and Ph.D students grasp the current direction of development and applications in the general Knowledge Service Engineering areas. The seminar courses are offered consequtively as a set through two semesters and are one of the mandatory courses in the department.