This course covers topics in managerial data mining, texting mining, and web mining, and related data retrieval and manipulation. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially focused course, students will learn when and how to use such techniques and how to interpret output. Students will also be introduced to languages such as R and Python to extract and manipulate data.

This course exposes students to how core business concepts are implemented in real-world organizational settings. Key business processes covered include procurement (materials management), fulfillment (sales), and production (manufacturing). The class meets in a computer lab and enables hands-on experience, with instructor guidance, to the ERP solution from SAP, the world's largest business software company. Using the system's core modules and data warehouse, students will gain insight into online transaction processing (OLTP) and online analytical processing (OLAP).

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

The service industry accounts for about 75% of the US employment and almost 60% of all personal consumption. This course will explore the service industries (e.g., transportation, health care, retailing, restaurants, and financial services) with a view toward developing models that allow planners to reduce costs and enhance customer service.

Recent advances in the areas of productivity and quality improvement. Specific topics include all or some of: ISO 9000, Total Quality Management, Lean Thinking, Materials Requirements Planning (MRP), and miscellaneous techniques from Just-in-Time. If time permits, topics from one or more of the American Production and Inventory Control Society's (APICS) certification exams for the CPIM (the Operations Management counterpart to the CPA in accounting). Includes team field project at a local company.