Online Business Courses From the Martin J. Whitman School of Management
Courses from the Whitman School’s online business programs are designed by the same renowned faculty members who teach on campus. All business course descriptions are listed below along with the technical courses offered in collaboration with the School of Information Studies (iSchool) and the College of Engineering and Computer Science.
Accounting analytics including Benford’s Law, current and prior period data, anomaly detection, correlation and time series detection, risk assessment and risk scoring, and purchasing card transaction fraud.
Advanced Topics In Auditing, Accounting, Fraud & Ethics
This case-based course enables students to look at advanced topics in auditing through the spectrum of significant audit failures. Cases will cover four major topics, including (1) fraud: violation of accounting principles, (2) ethics and professional responsibility, (3) fraud and inherent risk, and (4) violations of internal control. This course is an opportunity for students to apply the principles that they learned in their undergraduate auditing course to real-life situations in practice.
Audit practice and reporting on financial statements. Audit standards; the demand for auditing; and regulatory, legal and ethical influences on auditors. Audit objectives, evidence, control environment and risk assessments. Case studies and problems.
This course is intended for the graduate student who is interested in developing a portfolio of skills in business analytics. Class discussions will be based on case situations and on articles from business and technical publications. The class will include substantial hands-on work in data collection, analysis and interpretation.
Students will gain advanced hands-on experience with a number of analytical tools, including advanced Microsoft Excel, Microsoft Access, Google Analytics, R Programming and Tableau data visualization. Specific Excel topics covered include data manipulation, regression, financial modeling, dashboards and sensitivity analysis.
Examination of the application of entrepreneurship concepts and behaviors within established organizations, assessment of factors contributing to a company’s entrepreneurial orientation, and identification of ways to foster higher levels of entrepreneurship within firms.
In-depth examination of costing products and services, and using cost information in planning and control decisions. Pricing, budgeting, standards, strategic cost systems, just-in-time/backflushing costing and activity-based costing.
This course will familiarize students with the assumptions underlying various statistical techniques and assist in identifying their appropriateness in a variety of situations. Students should be able to perform statistical analysis and interpret results in a meaningful way. Students are expected to relate results of such analyses to become information-based decision makers.
Financial Accounting provides students with an understanding of the theory, concepts, principles and practices underlying the preparation of financial statements. Students will also develop the ability to interpret financial statements. Since this course is intended to assist the student in professional preparation, students will be expected to develop their communication, analytical, problem-solving and technical skills.
An introduction to methods and tools useful in decision-making in the financial industry, including macroeconomic event studies, analysis of term structures, Morningstar equity data, style analysis, credit card receivables, trading analytics, execution algorithms, etc.
This course is designed to provide an in-depth look at the analysis of public company financial statements from multiple perspectives, with a major focus on that of the shareholder. There are many courses and sources of information that show curious individuals how to calculate and interpret various financial statements, metrics and analyses. However, this course was put together understanding that there is a more important, qualitative side to analysis.
Throughout the program, students will learn to take information given by the markets and firms and adjust it to a more realistic base—and from that start, to create analysis that has value, not just a number.
The process of entrepreneurship in startup and established corporate environments. Approaches entrepreneurship as both attitudinal and behavioral, with applicability in a variety of contexts. Global dimensions of entrepreneurship are investigated as they relate to the independent and corporate entrepreneur.
The purpose of this course is to explore the interfaces between and among management, strategy and entrepreneurship in independent, corporate and nonprofit ventures. The focus is on the mastery of competencies that foster innovation and growth.
This course in global entrepreneurial management places unique demands on you due to its cross-disciplinary and interfunctional nature. It requires you to address many dimensions of your management education, including marketing, human resource management, finance, accounting, information technology, production, operations, supply chain management and managerial economics. In addition, many broader aspects of your liberal arts and social science backgrounds are relevant in this course. As such, it acts as a vehicle for acquiring knowledge and developing skills, attitudes and behaviors associated with innovative and strategic management in entrepreneurial environments.
Accounting concepts and standards. Topics include accounting cycle; income determination; financial statements; and measurement and valuation of assets including cash, investments, receivables, inventory, property, plant, equipment and intangibles.
Accounting concepts and standards. Topics include accounting cycle; financial reporting; financial statement analysis; cash flows; income tax allocation; measurement and valuation of liabilities; and equity, leases and pensions.
The implications of differences in international financial reporting practices for financial analysis and decision making. Foreign currency translation, mergers and acquisitions, transfer pricing, taxation, derivatives, and risk management.
Designed for students with little or no prior programming experience, this course will equip you with a working knowledge of the foundational business analytics operations in the Python programming language. Inspired by traditional bootcamps, the Introduction to Python for Business course was developed in partnership with industry experts and is taught through a combination of primarily synchronous instruction with a variety of hands-on project work.
Six Sigma process-improvement approach focused on quality, reliability and value to customers. Skills include techniques from the define, measure, analyze, improve and control (DMAIC) approach. Lean concepts from supply chain management.
The goal of this course is to provide students and their businesses with information that can prevent legal conflicts. Through a multi-faceted curriculum, students will learn to understand and appreciate the interrelationship between law and business. While the course is not intended to make students legal experts, it will help them analyze legal problems, recognize how law influences business and management decision making in these areas, and improve their management skills when faced with legal issues.
During the first sessions, lessons focus on understanding basic legal terms, the procedural context of litigation, and the legal system in general. Students also work on developing skills for critical thinking, problem solving and legal analysis. For the balance of the semester, the course will explore management decision making in situations that have legal implications.
This course focuses on helping students differentiate managerial accounting, its uses and applications from their experience in financial accounting. Students will learn terminology, operational strategies and problem-solving techniques utilized by management accountants, and learn to apply them to real-world management decisions.
This course deals with the principles of corporate finance. It will provide you with the language and the tools of finance and give you the capacity to understand the theory and apply, in real world situations, the techniques that have been developed in corporate finance. We discuss the three main principles that guide corporate managers in maximizing firm value: (1) the investment principle, (2) the financing principle and (3) the dividend principle.
The major topics of the course include the role of corporations and financial managers, time value of money, valuation, capital budgeting, hurdle rates, capital structure, and dividend policy. While focused on the corporate setting, this course will also help you to make better decisions in your own financial matters and it will familiarize you with how financial markets work.
Marketing analytics techniques including discriminant analysis, logit, cluster analysis, factor analysis and conjoint analysis. Marketing decision support models such as new product diffusion, test-market, price and sales promotion decision models.
Marketing Management provides students with an understanding of the theory, concepts, terminology and frameworks used by marketing managers to develop an organization-wide customer orientation. It provides insight into how strategic planning, analysis of the competitive environment, market research, market segmentation, target market selection and product positioning serve to create value for customers and the firm.
Finally, the course enables students to investigate how effective marketing plans integrate the four components of the Marketing Mix (product, pricing, placement and promotion) to optimize customer lifetime value.
Managing Sustainability: Purpose, Principles, and Practice
There is broad agreement that human activities are changing the natural environment. In addition, over-consumption of resources supplied by natural ecosystems has impaired the foundation of human activity. This online course incorporates some of the learning from popular residency trips to Dubai and Costa Rica to understand how their businesses and governments are promoting sustainable enterprises.
This course provides students with both the framework and technical expertise to collect, analyze and implement market research. They will learn the different types of data that drive marketing decisions, and learn essential skills such as exploratory research, market sampling, cross-sectional research and building regression models.
This intensive course teaches students a new way of thinking about microeconomics, not only exploring fundamental topics, but also teaching them how to understand relationships among them. The course covers microeconomic foundations and explores variations, including comparative statics, marginal analysis, market structures, information and externalities. Students will also explore policy implications and macroeconomic fundamentals, including money and national income measures.
Today, information technology is at the forefront of corporations seeking to increase and maintain competitive advantage in their industries as well as the global marketplace. The Introduction to IT & E-Commerce course will deepen students’ understanding of what IT is; how it helps lead/support business strategy, product development, operations, and business process; and how it provides opportunities for new business growth. The course will identify current/leading technology trends, and how those trends can help provide definitive benefits to corporate profitability.
This course is intended for the MBA generalist and will assist students with understanding the overall IT environment (strategic, organizational, technological and managerial) from an “Executive Perspective,” enabling them to develop the knowledge, skills and capabilities necessary to help make IT decisions as future managers or executives.
A collection of interdependent operating systems, or processes that transform inputs to outputs, lies at the core of most organizations. Organizations use these processes to acquire resources, transform them to produce goods and services that meet or exceed their customers’ expectations, deliver those products and services, and then support them over their life cycle. Supply chains are linked operating systems that typically extend beyond organizational boundaries.
Operations and supply chain managers oversee the transformation processes and the flows within and between adjacent operating systems. They direct and control the supply chain’s productive resources, including its labor, capital, information, materials and processes, to help it achieve the strategic objectives of the participating organizations. Usually, these objectives are attained by designing, producing, delivering and supporting desirable goods and services to customers, on time and to specification, at a cost that ensures adequate returns on invested capital.
This course introduces you to the field of supply chain management from an operations perspective. It surveys the terminology, concepts, problems and tools that support decision-making in the context of four major supply chain processes: obtaining inputs, including materials and support services; transforming these inputs to create finished goods and services for delivery to the next stage in the supply chain; processing customer orders and delivering the desired outputs to customers; and supporting/servicing those outputs after delivery.
Nature of occupational fraud and abuse in organizations. How and why occupational fraud is committed, detected and deterred; how to proceed if fraud is suspected. Emphasis on asset misappropriation schemes, corruption and financial statement fraud.
Managers are, first and foremost, problem solvers and decision makers. Decision making is typically difficult because it involves conflict and tradeoffs among the possible alternatives, of which some may be hard to recognize. Management science is a discipline founded on the principle that by abstractly modeling how our decisions affect outcomes of interest, we can make better, faster and more consistent decisions.
This course is an introduction to modeling for managerial decision making. It emphasizes the formulation, solution, interpretation and limitations of linear programs, network models, integer programs, non-linear programs, simulation and queuing models for tactical and strategic business decisions related to supply chain management. To facilitate understanding and communication of the various models discussed in class, the course will make extensive use of spreadsheet-based applications for prescriptive and descriptive mathematical models.
Tax planning and taxation of business transactions, such as basis, gains, losses, nontaxable exchanges, depreciation, amortization, other business deductions and tax credits. Research and communication skills.
This course is intended for the graduate student who is interested in developing a portfolio of skills in general project management. Students will learn core processes used by successful project managers, such as determining project scope, estimating costs and schedules, organizing and staffing a project, monitoring project progress, and developing lessons learned from completed projects.
Strategy and its integrative role in management. Concepts, models and skills for developing strategies to create and sustain competitive advantage in a dynamic and global environment. Topics include environmental analysis, strategy formulation and strategy implementation.
Concepts and tools essential for performing the role of a brand manager in a dynamic and competitive market. Coordinating marketing activities to achieve a profitable and sustainable market position of the brand.
This course explores the impact that strategic sourcing has on the success of both small and large-scale businesses. Students will explore topics such as the strategic nature of purchasing, negotiating tactics, international sourcing and cutting-edge technology used in “world class” purchasing departments. In addition, students will take a deeper look into the ethical, contractual and legal issues faced by purchasing professionals.
Influence of supply chain management and logistics on corporate strategy and profitability. Topics include transportation economics and operations, customer service, and international logistics, as well as other related topics.
Incorporating tax costs and benefits into business planning and decision making. Highlights the problems of entrepreneurs, transfers of businesses, financial reporting effects, business life cycle and entity choice, and international operations.
Financing issues as they relate to entrepreneurial ventures. The financial needs and financing strategies of growth-oriented ventures are highlighted. Stages of entrepreneurial finance are investigated. The roles of valuation, deal structures and negotiation tactics are explored.
Technical courses offered in collaboration with the School of Information Studies and the College of Engineering and Computer Science
Introduction to Data Science
The course provides students with a hands-on introduction to data science, with applied examples of data collection, processing, transformation, management and analysis. Students will explore key concepts related to data science, including applied statistics, information visualization, text mining and machine learning. R, the open source statistical analysis and visualization system, will be used throughout the course. R is reckoned by many to be the most popular choice among data analysts worldwide; having knowledge and skill with using it is considered a valuable and marketable job skill for most data scientists.
Students will also learn how to use supervised and unsupervised machine learning techniques. They will focus on structured data, using R (e.g., support vector machines, association rules mining) in conjunction with learning the full life cycle of data science.
This course offers a broad introduction to analytical processing tools and techniques for information professionals. Students develop a portfolio of resources, demonstrations, recipes and examples of various analytical techniques while growing their specialization in one or more areas of interest.
Students will learn to obtain, screen, clean, link, manipulate, analyze and display data while creating summaries, overviews, models, analyses and basic tables, histograms, trees, and scattergrams. They will use Python and Apache Spark to explore classic and modern machine learning techniques (such as deep learning) within a big data context, including sentiment analysis via supervised learning, recommendation systems via unsupervised learning and predicting credit scoring via random forest machine learning.
This course introduces data mining techniques, real-world applications of those techniques and their challenges. Students learn popular data mining methods to gain insight from data and solve complex issues across industries.
Students also acquire hands-on experience using current software to develop data mining solutions to scientific and business problems. Topics include the key tasks of data mining. Through the exploration of the concepts and techniques of data mining and practical exercises, students will develop skills that can be applied to business, science or other organizational problems. Additionally, students will use R and other open source tools to perform machine learning across a range of situations when working with structured data (including clustering, classification, decision tree and association rules).
This course is a broad introduction to data visualization for information professionals through demonstrations, recipes and examples of various data visualization techniques. Students are introduced to the programming language R, Adobe Illustrator, simple data cleaning techniques, simple design concepts and the ethics of visualizing data. The focus is on developing static data visualizations to visually explore and communicate findings using data from a variety of sources. Conceptual themes are presented alongside technical aspects of data visualization.
This course introduces the concepts of business intelligence (BI) and the practice/techniques in building a BI solution. Students focus on how to use data warehouses as a BI solution to make better organizational decisions. Topics include concepts, principles and tools for designing and implementing data warehouses.
Students learn the differences between Ralph Kimball’s and Bill Inmon’s approaches, roles and responsibilities in the design and implementation of a data warehouse, project management guidelines and techniques, and requirements gathering. Coursework also covers dimensional modeling, Extract Transform and Load (ETL) architecture, specification and data loading, and master and reference data management, as well as integration approaches (ETL, EII, EAI), analytical reporting concepts, data governance and recent trends in the data warehouse domain.
This course introduces database management system (DBMS) building blocks; entity-relationship and relational models; SQL/Oracle; integrity constraints; database design; file structures; indexing; query processing; transactions and recovery; and an overview of object relational DBMS, data warehouses and data mining.
Introduction to data mining techniques, familiarity with particular real-world applications, challenges involved in these applications and future directions of the field. Optional hands-on experience with commercially available software packages.
Data Administration Concepts and Database Management
This course provides a foundation for database administration, exploring the fundamental models of database management systems. It covers the definition, development and management of databases for information systems. Students learn data analysis techniques, data modeling, schema design, query languages and search specifications, including Structured Query Language (SQL); data structures; file organizations; principles of data management systems; and hierarchical, network and relational data models.
Students gain hands-on experience using Microsoft’s Access and SQL Server database management systems (DBMS) as implementation vehicles. This course provides hands-on experience in database design and implementation through assignments, lab exercises and course projects. This course also introduces advanced database concepts such as transaction management and concurrency control, distributed databases, multitier client/server architectures, web-based database applications, data warehousing, and NoSQL.
This course focuses on the linguistic and computational aspects of natural language processing (NLP) technologies. Students develop an understanding of how NLP can process written text and produce a linguistic analysis that can be used in other applications. Discussions cover the multiple levels of linguistic analysis required for a computer to accept natural language input, interpret it and carry out a particular application. Topics include levels of linguistic analysis with a focus on techniques in application.
Students in this course will explore all the levels of linguistic analysis, going from tokenization, word-level semantics, part-of-speech tagging, syntax and semantics up to the discourse level. They will also use NLP techniques on unstructured data using Python, including information retrieval, question-answering, sentiment analysis, summarization and dialogue systems.
Students are immersed in object-oriented programming principles and techniques using C++. Topics and project work include classes, overloading, data abstraction, information hiding, encapsulation, inheritance, polymorphism, file processing, templates, exceptions, container classes and low-level language features. Students will develop the skills required to map C++ to GUI, databases and real-time programming.
This course covers a broad spectrum of software engineering topics. Students will work through the complete software engineering process, models in software engineering, requirements and specifications, design techniques, functional decomposition, data flow, data structures, theoretical issues in testing, testing strategies, and cost and reliability models. The course is based entirely on a practical industry perspective, including current industry standards and usages for concepts covered in class. Students will emerge from the course with the knowledge and skills necessary to quickly learn, adapt to or modify an organization’s specific software development processes.