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Online MBA in Business Analytics Curriculum

Curriculum Details

33 total credits required

Throughout the 11 courses in the online MBA in Business Analytics program, you will develop robust skills in business analytics and engage in hands-on experience with analytical tools. The program is consistent with industry certifications, including the Certified Analytics Program (CAP) and Associated Certified Analytics Program (ACAP), and thoroughly prepares students for both certification exams. Because of the overlap in curriculum with Lebanese American University’s Global MBA program, students get expanded networking opportunities through interaction with students from both programs.

The extensive list of course options allows you to tailor the curriculum to your needs, including qualitative and quantitative analytics options. In the capstone course and industry partnerships in the Lebanon region, you’ll have the opportunity to apply practical skills and knowledge gained in the program, preparing you for real-world business scenarios.

Core

This course examines real world examples of how insights gained through analytics to significantly improve a business or industry. Through our tour of real-world transformations driven by analytics, students will gain knowledge in the use of descriptive, diagnostic, predictive, and prescriptive analytics models.

The applications studied in this course rely heavily on predictive and prescriptive analytics tools. Students will learn how to define business problems requiring prediction and then select the most appropriate forecasting strategy to meet the application. Similarly, students will learn how to frame a decision problem and then select and apply the appropriate data driven decision making strategy.

Covers statistical and business analytics tools useful for making effective managerial decisions in a disorganized and uncertain environment in all functional areas of business. Students learn the essential statistical topics of description, probability, inference and regression, and how to apply them using Microsoft Excel. They learn how to choose appropriate statistical methods in realistic business contexts and how to interpret and effectively communicate results. Students also learn how to use data visualization tools, pivot tables and charts, data tables, optimization models and Monte Carlo simulation.

The capstone course focuses on the use and application of the various descriptive, predictive and prescriptive analytics methods for solving real life business problems. Students will apply the business analytics tools, knowledge and skills to solve an actual business problem. They will report and present their findings and recommendations. Emphasis is given to integrating the business analytics concepts and ideas to provide a perspective on how a company can apply fundamental data analysis to derive the actionable business decisions. 

Elective (Business Administration)

The objective of this course is to provide an understanding of financial accounting fundamentals for prospective consumers of corporate financial information, such as managers, stockholders, financial analysts, and creditors. The course focuses on understanding how economic events like corporate investments, financing transactions and operating activities are recorded in the three main financial statements (i.e., the income statement, balance sheet, and statement of cash flows).

This course is an overview of microeconomics from a managerial decision-making standpoint, emphasizing and applying the basic concepts to selected problems. Topics include the firm’s behavioral and managerial theories, determination of national income, demand estimation, cost determination, forecasting, and government regulation.

This course introduces students to corporate finance principles and applications. It covers the following topics: (1) Financial Statements; (2) Cash Flow Estimation; (3) Time Value of Money; (4) Capital Budgeting Methods; (5) Valuation of Bonds and Stocks; (6) Risk and Return; and (7) Cost of Capital.

This course shows students how to manage the marketing process for organizations, to optimize the resource use and to maximize the benefits. It focuses on decision-making. Lectures, case studies, discussions and projects engage students in learning how best to manage scarce resources.

Tourism is one of the largest global industries and a major source of cross-cultural interactions and cultural change. This course provides theoretical understandings of tourism’s economic, environmental, and social benefits and impacts on local communities and environments, using case studies to illustrate various types of tourism in several regions of the world.

This course covers global business, ethics, social responsibility, and legal systems. Business in the global environment is comprised of many factors: the parts played by governments, international institutions, regulations, world monetary and trade systems, global ethics, social responsibility, cultural diversity, differences in opportunities, environmental concerns, economic development, technology, economy, and education among others. The course discusses the conflicts among corporate beneficiaries and socially responsible corporate responses.

Students will experience a foundational as well as practical approach for developing a social media plan. In addition, students will gain technical hands-on experiences by using interactive simulations and conducting real life projects related to social media platforms.

The objective of this course is to provide you with the latest world-class knowledge of major frameworks, theories, and research findings in the trending field of digital marketing. The goal of this course is not to simply learn the material, but rather it is to integrate and apply it. By the end of this course, students will be able to design and implement digital marketing strategies for companies, taking into consideration their global scale and the different markets they operate in. Emphasis will be placed on understanding the Omni-channel shoppers’ & e-retailers’ motivations, crafting effective digital strategies, making efficient use of the virtual environment in the global marketplace.

This course is an examination of research methods applicable to the identification, definition, and problem resolution in a business environment, emphasizing methodological aspects and data collection and analysis techniques. Topics include problem identification and definition, hypothesis formulation, selection of appropriate research designs, sampling, data collection methodologies, statistical validation, and research report writing.

This course is an introduction to the application of mathematical techniques in business decision-making, emphasizing practical usage in management situations. Topics include linear programming, transportation problems, network planning, queuing theory, regression analysis, and modeling techniques.

Elective (Business Analytics)

This course offers students an understanding of the “data” or the conscious/non-conscious information processing in our brains explaining the consumer’s decision-making on a non-conscious level. Neuro-metrical and biometrical measures, models and technologies help students understand and predict consumer behavior using non-traditional research methodologies.

Cognitive analytics is about understanding brain science (neuro-science, behavioral economics & social psychology) and exposing as well as measuring the consumer’s hidden data from the mind and body. Applying data mining techniques to Neuro Marketing data (mind-mining) will provide students with a much deeper and richer understanding of consumer preferences, choices and behavior.

This course provides an understanding of the business value of big data, the importance of effective management of big data, and the development of technical competencies using leading-edge platforms for managing and manipulating structured and unstructured big data.

Topics include data cleaning, and exploration; predictive models, linear and nonlinear regression models, decision tree analysis, and discriminant analysis; resampling techniques; clustering analysis and dimension reduction. Applications to marketing, operations, finance, and risk management.

This course covers key risks to information systems and business data. Students will apply data analytics techniques across different dimensions to provide effective information security analytics. Threats to normal user behavior are compared and contrasted by utilizing the user behavior analytics approach Normal behavior.

This is an introductory course to the healthcare research fundamentals and methodologies. Topics include healthcare research design, data collection, data analysis, and operations research and operations management tools applied to the health care management sector.

This course examines the ethical aspect of business analytics. It covers topics in data ethics regarding the moral obligations, values and principles governing data protection and privacy rights. It also explores how data driven decisions can have a profound impact on society and how businesses can refine their strategy to learn from past mistakes and built on previous successes.

An introductory course to data visualization. It covers visualization techniques applied to extract information that aids in the data driven decision-making process. Students will use various visualization tools to visually explore business problems, develop data visualizations, dashboards, and stories. Students will focus on communicating the results in an effective and informative manner.

This course provides a framework and tools for managing and analyzing an organization’s digital presence for marketing purposes. This highly technical and analytical course applies concepts of social media marketing in practice through applicable projects and assignments. Students are given the opportunity to experience and analyze the effects of creating, promoting, and adapting marketing activities so as to measure their effects on the company, as well as global markets the brand operates in.

Selected advanced topics in business analytics topics. Topics include ethics in analytics, supply chain analytics, financial analytics, entrepreneurial and innovative approaches to problem solving, human resources analytics, and effective communication & reporting.

This course entails the application of research methods to a current topic relevant to business analytics. The thesis must incorporate the student’s hypothesis, test methods, test results, and conclusions, in a report available to later researchers. In some cases, the faculty may authorize expanded research procedures resulting in high-quality publication.

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