This course is designed to prepare students for success in the following career and professional development competencies such as networking, internship/job search, professional etiquette and industry research. Specific activities will include but are not limited to: resume building, interviewing skills, dressing for success, utilizing social media platforms, developing elevator pitches, building professional connections, increasing knowledge of industry and career areas and navigating career fairs.

This course is designed to teach future leaders what they need to know in order to build high-performance operations with world-class processes, continuous improvement and innovation. We cover the most cutting-edge methodologies and tools, together with the most important soft skills required, to create lean and responsive operations that deliver the highest quality services and products.

The Artificial Intelligence in Business is designed for business major students aspiring to develop a deeper understanding of artificial intelligence and its use in business applications. The course will provide an introductory overview of different mathematical and computational data analysis tools and machine learning techniques commonly used in artificial intelligence. Focus will be on case studies and applications that demonstrate how artificial intelligence can augment current business operations.

The Artificial Intelligence in Business is designed for business major students aspiring to develop a deeper understanding of artificial intelligence and its use in business applications. The course will provide an introductory overview of different mathematical and computational data analysis tools and machine learning techniques commonly used in artificial intelligence. Focus will be on case studies and applications that demonstrate how artificial intelligence can augment current business operations.

Quality control concepts including: fundamental computer and statistical concepts: Statistical Process Control (SPC) using control charts; methods for quality improvement; acceptance sampling; industrial experimentation and reliability.

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. Theoretical background in descriptive and inferential statistical methods will be used support knowledge of the appropriate statistical test to perform in a given situation. The statistical methods that are covered in the course equip the student with the analytic reasoning and quantitative arguments that applies to all areas of business and management.

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.

In the digital age, the ability to analyze and interpret marketing data has become essential for success. This course, Applications of R for Marketing and Analytics, is designed to equip students with the skills needed to harness the power of data in making strategic marketing decisions. Through a blend of theoretical concepts and hands-on practice, students will learn how to clean, analyze, and visualize marketing data from real world datasets. Students will acquire knowledge about the methods and software that are used to understand issues such as market segmentation, sales forecasting, and conjoint analysis.

Marketers use a broad array of evolving tools, from Direct Mail to Social Media. In this course, students learn about the range of these tools, related data sources, and online and offline metrics for evaluating their success. The course stresses combining different marketing resources (for example, bricks and mortar stores with online channels; online landing pages to test offline media with google analytics).