Danish Saifee, PhD

Theories and techniques of database design, implementation, and application for data resource management. Topics include data structure techniques for databases, data modeling techniques, logical database design, physical database design, SQL, distributed database, and data warehouse.

Introduction to the information technology used in modern organizations. The course is designed to provide a technical understanding of information technology, practical experience and management perspectives on its utilization in organizations.

Introduces graduate business students to the concepts, applications, opportunities, and limitations of artificial intelligence (AI) in organizational settings. The course examines conventional machine learning (ML) approaches such as regression, classification, decision trees, random forests, and clustering, as well as deep learning (DL) approaches including neural networks, convolutional neural networks, recurrent neural networks, transformers, and generative AI. Emphasis is placed on understanding how AI models work, how they are evaluated, the business problems for which they are appropriate, and the managerial, ethical, and governance issues associated with their use. Particular attention is given to foundational concepts and analytical frameworks that remain valuable despite the rapid evolution of AI technologies and platforms. The course is designed for business students and does not require prior programming experience.

Business intelligence (BI) and knowledge management (KM) issues facing technology management today and information technology needed to solve managerial problems using BI and KM. Concepts of BI and KM, processes of BI and KM, and the integration of BI and KM are discussed.

Business intelligence (BI) and knowledge management (KM) issues facing technology management today and information technology needed to solve managerial problems using BI and KM. Concepts of BI and KM, processes of BI and KM, and the integration of BI and KM are discussed.