This course provides an understanding of the strategic role of Information Technologies (IT) in business; how to successfully integrate IT into the organization; how to manage the challenges associated with conceiving, justifying, implementing and maintaining IT-based initiatives ; and how to be an active and productive participant in management decisions that involve IT.

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.

Overview of human resource management theory and practice in organizations. Legal framework; job design; recruitment, selection, performance appraisal, and separation; compensation; benefits; contemporary issues in HRM.

This course covers essential concepts and methods to foster data-driven decision-making to motivate business insight and innovation. Lessons cover topics in big data, algorithmic thinking, machine learning, data visualization, and communication. Projects spanning several weeks focus on business problems that can be solved through the application of cutting-edge Data Science techniques. Students develop proficiencies in the use of Python, R, and Tableau by completing regular exercises and projects using real data.

This course covers essential concepts and methods to foster data-driven decision-making to motivate business insight and innovation. Lessons cover topics in big data, algorithmic thinking, machine learning, data visualization, and communication. Projects spanning several weeks focus on business problems that can be solved through the application of cutting-edge Data Science techniques. Students develop proficiencies in the use of Python, R, and Tableau by completing regular exercises and projects using real data.

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications.

This course reviews the foundations of modern economics with an emphasis on its applications in business. Course coverage includes a range of both microeconomic and macroeconomic subjects. Topics include demand and supply analysis, consumer theory, theory of the firm, unemployment, inflation, monetary and fiscal policy, economic growth, the causes and consequences of recessions, and issues in global economics.

The purpose of this course is to introduce students to the area of corporate finance and investments. Students will learn about the basic concerns and responsibilities of financial managers, and gain an appreciation of the methods of analysis employed by them. Students will learn both theory and practice of corporate finance and investments.

The purpose of this course is to introduce students to the area of corporate finance and investments. Students will learn about the basic concerns and responsibilities of financial managers, and gain an appreciation of the methods of analysis employed by them. Students will learn both theory and practice of corporate finance and investments.

This course builds upon the content covered in Exploring Data Analytics for Accounting Professionals, by continuing to develop the skill set and approaches needed to be an analytically-minded accounting professional. Students will learn how to assess and communicate business problems, to evaluate and analyze data and to develop and effectively present data-driven recommendations.