This course provides an introduction to applications of Python for business analytics. This class will focus on data extraction and manipulation as well as automating data analysis tasks to support the larger goal of improving business outcomes through data-driven insights. No prior programming experience expected.

An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

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.

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.

Examines information technology from a business enterprise perspective. Topics include: the components and development of business information technology systems, their use in enhancing and facilitating management practices and decision making and their impact on management decisions.