Master of Business Administration with a concentration in Applied Business Analytics online

This course provides students with an introduction to basic accounting fundamentals and skills necessary to analyze financial information of firms from a decision-maker perspective. Financial information is presented in the form of financial statements, principally, the income statement, balance sheet, statement of retained earnings, and cash flow statement. We will discuss how accountants organize the results of business transactions and report them to external users who will then use the reports to make decisions.

This course will help students to develop a comprehensive analysis of the micro and macroeconomic forces that shape and modify our economy. Supply and Demand, Revenue and Cost, wages, employment, regulations and taxation are discussed as they affect production, consumption, investment, trade, prices, quantities, profits, inequality, and the economy as a whole.

A study of the basic principles and practices of financial management of private (as opposed to government owned or affiliated) business operations. The principles and models discussed in the course can be equally applied to publicly listed companies as well as privately owned ones. This course includes an operational framework for financial analysis, financial planning including capital budgeting, along with valuation analysis and cost of capital. The basic framework of analysis used is that of risk and return, emphasizing that the objective of the firm is to maximize shareholder return, subject to satisfying societal and other stakeholder concerns.

The main objective of this course is to introduce the basic statistical concepts and tools in order to form the foundation through which students can analyze data used for decision-making. The course is application-oriented and focuses on topics that are useful in business and industry such as descriptive statistics, probability, conceptual modeling, and problem formulation and decision analysis. The course prepares students to develop an understanding of how to deal with new trends in the industry such as big data and data mining.

This course takes a broad-based look at management and organizations in order to provide students with the building blocks needed for more advanced classes in the program. It exposes students to the history of management thought and to some of the most influential organizational theories. It uses insights from multiple disciplines such as economics, sociology, anthropology, psychology, and political economy and offers frameworks for analyzing modern organizations and current managerial practices. The course concludes with a discussion of contemporary issues in management.

Marketing is viewed as a system designed to create, capture, distribute, and communicate value to consumers and businesses. The course emphasizes the managerial approach to developing marketing strategy through analyses of business conditions, customers, and competitors. Emphasis is given to understanding buyer motivations, behaviors, and contexts as the basis for marketing decisions.

This course deals with the environment in which international business is conducted, including economic and financial relations, environmental and strategic factors that affect business operations within different nations. Topics include international trade, the balance of payment, exchange rate determination, hedging of foreign exchange exposure, tariffs and other trade restrictions, economic development, economic integration, and international economic organizations within different nations. Also reviewed are the economic, political and cultural conditions that influence international business.

Students may choose to investigate an issue at their place of work, undertake research that will lead them to new fields, or create proposals for business models or start-ups. The capstone experience will provide students with direct exposure into various industries and also serve as a basis for planning and advancement. Finally, the course will also help MBA candidates establish their professional identities through reflective assignments and self-assessments as guided by their instructor. The course is taken in the MBA student’s last semester, or after completing the majority of courses.

This course explores business analytics concepts and applications aimed at improving business performance. The course focuses on the three facets of analytics:  Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. An integral part of business analytics is the use of IT tools to support the collection and analysis of data, and converting it into actionable knowledge in the context of organization decision-making and problem solving. As such, the students will learn problem analysis and formulation, data modeling, data mining, and the application of various business analytics and spreadsheet tools.

The course studies strategic management from the perspective of environmental sustainability, with an emphasis on the impact of innovation on corporate social responsibility. Sustainable Strategic Management refers to strategic management policies and processes that seek competitive advantages consistent with a core value of environmental sustainability. Firms that pursue sustainable strategic management base the formulation, implementation, and evaluation of their strategies on an analysis of the ecological issues they face, the values they hold that support sustainability, and the ecological interests of their stakeholders.

Managers need resources to succeed, and successful managers tend to negotiate well to give themselves the best chance to succeed. They negotiate with customers and suppliers for better prices, and they negotiate with internal functions to get better support and key resources to deliver value to both internal and external stakeholders. As managers move up the corporate ladder, they negotiate with their team members for better commitment and they negotiate with their superiors for domain independence. This course will focus on managers’ need to influence others, manage conflict, and negotiate agreements in a wide range of business scenarios both within and outside the organization. Students will be introduced to basic theories of negotiation, practices and frameworks of negotiation. Students will be provided with opportunities to reshape their understanding of negotiation, discover their own negotiation styles, and apply negotiation principles to critical issues. The course takes a view that negotiation is also a life skill that comes in handy in career growth and addresses the managers need to understand that influencing often occurs without formal power or authority. The course uses a combination of lectures, discussions, role-play exercises, cases, and exams.

This course serves as a hands-on introduction to basic statistical concepts and the ways to communicate them to the target audience. Currently, businesses encounter tremendous challenges to process and utilize the vast amounts of different types of data generated as a result of customer and business activities. This class introduces the fundamental elements of inferential statistics and supplements it with visualization techniques to show students how to learn, analyze, and present data. The focus on inferential statistics will enable students to describe data, evaluate samples, and perform hypotheses testing. Visualization techniques will help students communicate their findings in the form of reports and presentations.

This course includes the principles of programming and software development using Python programming language. This class emphasizes the applications of computer programming based on real-life examples in various fields of business including Business Analytics, Management, Marketing, Finance, among others. Upon completion of the course, students will be able to understand computational concepts in addition to the fundamentals of the Python programming language. In addition, this course will cover the manipulation and use of data to solve businesses problems. In this course, students will be introduced to software packages for data manipulation and development of solutions to statistical and mathematical problems. In addition, we will apply machine learning and statistical methods to data obtained from online sources.

This course covers two related topics in the age of big data and knowledge discovery: data warehousing and data mining — their concepts, principles, and techniques. Topics in data warehousing include data warehouse/data mart architecture; multi-dimensional model design; extracting, transforming, and loading strategies. Topics in data mining range from statistics to machine learning; including techniques of clustering, association rules, and classification. OLAP (On-Line Analytical Processing) applications and business intelligence are also introduced.

This course is designed to provide a broad overview of machine learning concepts and applications aimed at automating and advancing analytics performance. The course distinguishes itself by anchoring its content on big data phenomena and thus domain knowledge, technology, and math are integrated throughout the course. The course covers five broad segments of topics in machine learning driven analytics: Fundamentals (Algebra, Matrices, and Probability for ML), algorithms (Optimization Techniques), supervised learning, unsupervised learning, and managerial application (Thought Leadership and usage of ML in big-data analytics). This course provides a unique balance between theory and application along with data driven cases — thus it aims to impart expert skills along with encouraging thought leadership. An integral part of machine learning analytics is the use of IT tools to support the organization and analysis of data — hence the students will learn to apply various machine learning analytics tools including R.

This course provides a practical introduction to concepts, processes, and methods deployed in the field of artificial intelligence (AI). AI applications are currently deployed in a vast range of business activities for the purpose of employee vetting, answering customer queries, target marketing, predicting and assessing loan risks, warehouse management, and customer delivery management. Upon completion of this course, students will be able to understand AI processes and apply analytics tools such as Python and R to solve business problems and develop applications.