Teaching And Curriculum Development Activities

The University of Tulsa (student responses were typically more than 4.5 on the five-point scale, evaluations available upon request)

Operations Management (MBA 7033): Demonstrate knowledge in the fundamental concepts and tools about managing operations and how operations affect people, organizations, and society.

Essential topics include process analysis, analytical decision-making, inventory and quality management, analytics, and management science.

Foundations of Analytics (QM 7073): Survey of the concepts, principles, and foundational ideas about data that teach data mining and analytics in professional business settings. This course provides knowledge and applications of descriptive, predictive, and prescriptive analytics.

Data Mining and Predictive Analytics (QM 7063): Introductory survey of the technologies used to uncover patterns and associations in large databases. The goal is to understand business situations better and improve business decision-making. While data mining techniques can be applied to various disciplines, this course specifically focuses on improving business processes and performance. Applications will focus on various business problems and activities, such as fraud detection, market basket analysis, cross-selling, churn, market segmentation, credit rating, process management, and sports management. Students will gain hands-on experience in using computer software to access and mine business data sets. The primary tools used in the class are the Python or R programming language and several associated libraries.

Enterprise Data Systems (QM7093): Concepts of data modeling, data architectures, and data administration. Study various models with Investigation of enterprise-wide data systems that support and facilitate data analytics and business intelligence.

Analytics Programming (QM 7103- New course development): Expose students to the analytics programming languages, R and Python. A programming background is plus but not required. You will learn the fundamental concepts of R and Python Programming languages, perform data manipulations, code essential functions, implement basic calculations in RStudio and Python Jupiter Notebook environment, and perform the workhorse analytical tasks such as data preprocessing and explanatory data analysis.