Courses

The listing of a course description here does not guarantee a course’s being offered in a particular semester. Please refer to the published schedule of classes on the Student Link for confirmation a class is actually being taught and for specific course meeting dates and times.

• QST AC 848: Intermediate Accounting 2
  This course focuses on the recognition and measurement of issues in accounting related to income taxes, lease obligations, and pension liabilities and equity. It focuses further on the preparation of, and uses for, statement of cash flows; calculating, reporting, and interpreting financial measures, including earnings per share; the nature and purpose of segment and interim reporting; and accounting for changing prices. The course also provides a brief overview of the auditor's opinion.
• QST AC 860: Accounting Risk Management
  The objective of this course is to provide students who have no previous accounting knowledge with the accounting tools necessary for a better understanding of a firm's fundamentals, to enable a meaningful economic assessment of the firm's risk and potential return.
• QST AC 865: Auditing Issues & Problems
  Introduces the basic concepts underlying auditing and assurance services (including materiality, audit risk, and evidence) and demonstrates how to apply those concepts to audit and assurance services through financial statement audits.
• QST AC 869: Principles of Income Taxation 1
  Federal income tax law common to all taxpayers--individuals, partnerships, corporations. Tax returns for individuals. Topics include tax accounting, income to be included and excluded in returns, tax deductions, ordinary and capital gains and losses, inventories, installment sales, depreciation, bad debts, and other losses.
• QST AC 879: Income Taxation II
  Certain common and special Federal tax laws for individuals, partnerships, corporations, estates, trusts, and miscellaneous entities. Topics include income tax returns for partnerships, business corporations, special corporations, decedents, estates, and trusts. Survey coverage of corporate liquidations, pension and profit-sharing plans, IRS audits, and estate and gift taxes.
• QST AC 898: Directed Study: Accounting
  Graduate-level directed study in Accounting. 1, 2, or 3 cr. Application available on the Graduate Center website.
• QST AC 899: Directed Study: Accounting
  Graduate-level directed study in Accounting. 1, 2, or 3 cr. Application available on the Graduate Center website.
• QST AC 901: Introduction to Accounting Research
  Introduction to basic tools in financial accounting and managerial accounting research; domain of accounting research and research methods employed; using computerized databases in large sample financial accounting studies; basic managerial accounting modeling tools.
• QST AC 909: Contemporary Accounting Topics
  This course, required of accounting doctoral students, introduces several fields of contemporary accounting research and research methodologies which are not covered in the financial accounting, managerial accounting, and research methods seminars. This seminar is also intended to provide an opportunity for students to study interdisciplinary research involving accounting.
• QST AC 918: Financial Accounting Research
  This course, required of accounting doctoral students, covers contemporary research in financial accounting, reviewing major trends and addressing methodological issues in such research. The course emphasis is on development of skills in designing and executing research projects involving financial accounting.
• QST AC 919: Managerial and Cost Accounting
  This course, required of accounting doctoral students, covers contemporary research in managerial accounting. We review major trends in analytical and empirical research, including agency theory. Students are required to design a research project around a managerial accounting question.
• QST AC 990: Current Topics Seminar
  For PhD students in the Accounting department. Registered by permission only.
• QST AC 998: Directed Study: Accounting
  PhD-level directed study in Accounting. 1, 2, or 3 cr. Application available on the Graduate Program Office website.
• QST AC 999: Directed Study: Accounting
  PhD-level directed study in Accounting. 1, 2, or 3 cr. Application available on the Graduate Program Office website.
• QST BA 222: Modeling Business Decisions and Market Outcomes with Spreadsheets and Statistical Programming
  Examines the use of economic and statistical tools for making business decisions at an advanced level, and prepares students for future study in business analytics. Introduces programming for data analysis (no previous programming knowledge required) and links data analysis to decision making using both spreadsheet modeling and statistical programming. Topics include multiple regression, causal inference, forecasting, predictive analytics, machine learning, demand modeling, and optimization. Case studies apply advanced concepts to practical business problems. 4 cr. Effective Spring 2021, this course fulfills a single unit in the following BU Hub area: Quantitative Reasoning II.
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  • Quantitative Reasoning II
• QST BA 305: Business Decision-Making with Data
  Explores advanced business analytics topics, including risk and uncertainty, optimization, decision analysis, multi-attributes objective functions, and time tradeoffs. Links data models to strategy and ethics. Relies on both statistical programming and spreadsheet modeling and introduces novel techniques. Cases studies and projects apply topics to practical business problems.
• QST BA 472: Business Experiments and Causal Methods
  Formerly MK472. When is making a change to a price, algorithm, or product worthwhile? Rather than relying on the gut intuition of a manager, businesses are increasingly using experiments and other forms of causal data analysis to answer these questions. In this class, we will learn about causal methods, when they work, how to implement them in R, and how to apply them to digital markets. The business topics covered include pricing, balancing digital marketplaces like Airbnb and Uber, reputation systems, measuring influence in social networks, and algorithmic design.
• QST BA 476: Machine Learning for Business Analytics
  Formerly MK476. This course introduces students to the foundational machine learning techniques that are transforming the way we do business. Machine learning relies on interdisciplinary techniques from statistics, linear algebra, and optimization to detect structure in large volumes of data and solve prediction problems. You will gain a theoretical understanding of why the algorithms work, when they fail, and how they create value. You will also gain hands-on experience training machine learning models in Python and deriving insights and making predictions from real-world data. Prior programming experience is strongly recommended.
• QST BA 755: Describing, Analyzing, and Using Data
  This course focuses on how to learn from data, specifically to 1) organize, portray, and summarize data; 2) assess the validity of conclusions that have been drawn from statistical analyses to support business (and other) decisions; and 3) recognize the extent to which variation characterizes products and processes, and understand the implications of variation on organizational decisions when interpreting data. Students will increase their understanding of the use of probabilities to reflect uncertainty; how to interpret data in light of uncertainty to assess risk; and how to build and interpret regression models, which can be used to inform core business and organizational decisions.
• QST BA 765: Introduction to Programming for Data Science
  This course will cover the fundamentals of programming for data science using R, the command line, and version control. These skills will be reinforced via lectures and hands-on exercises focused on elevating common programming challenges and highlight best practices. The aim of this course is to provide the pathway to fluency in the tools required to analyze data and fully manage data science projects both as an individual contributor as well as in team settings.

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