Courses

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

• QST BA 860: Marketing Analytics
  Prerequisites: QSTBA 600, QSTBA 602, QSTBA 780, QSTBA 810, QSTBA 820, QSTBA 830. This is a course on analytics in digital marketing. The core of marketing is reaching your audience and communicating the value of your brand and products to them, so that you can grow and retain customers. Digitization offers a variety of new data and tools that makes this effort more accessible for large and small companies alike. This course aims to familiarize students with digital marketing analytic tools, as well as the mindset of focusing on incrementality when analyzing the effects of marketing strategies. We will introduce marketing tactics used in different stages of a customer's journey, including advertising, search engine optimization, pricing, and on-site marketing. In the context of these topics, we introduce analytic tools to measure marketing effects and optimize campaign efforts, including experiment design and analysis, targeting campaign design and assessment, recommender models, and attribution modeling.
• QST BA 865: Neural Networks in Business: From Foundations to Generative AI
  Prerequisites: QSTBA 600, QSTBA 602, QSTBA 780, QSTBA 810, QSTBA 820. This course provides a basic introduction to the theory and implementation of artificial neural networks (ANNs) in Python. We will introduce students to Keras and PyTorch, Python packages / frameworks that support the implementation of neural networks. We will then develop an understanding of fundamental concepts behind neural network architecture. We will explore a variety of use cases, deal with various types of unstructured data (text, images, audio, time series), and gain hands-on experience, starting with the implementation of simple networks and building up towards harnessing the powers of more complex pre-trained ones. This is an intensive course. Students will pursue a hands-on group project over the duration of the course.
• QST BA 870: Financial Analytics
  This is an introductory course on Financial Analytics providing students with knowledge about key "financial" concepts (financial accounting, financial statements, managerial accounting, corporate finance, and investments) so that they can intelligently apply their prior analytics knowledge and tools to real- world financial applications.
• QST BA 875: Operations and Supply Chain Analytics
  This is an introductory course on principles, methods, and techniques used in operations and supply chain analytics. Emphasis is given on the big data age where firms are continuously designing, assessing, and improving the systems that create and deliver their products and services. Students will learn visual representation techniques to enhance their understanding of complex data and models. Such visual techniques will be paired with network analysis to better identify patterns, trends and differences from datasets across categories, space, and time. The course will also draw on real-world applications to demonstrate their use in a variety of contexts.
• QST BA 878: Machine Learning and Data Infrastructure in Health Care
  This course is designed to provide students with a deeper understanding of the key concepts, methods, and tools in data science, machine learning, and data infrastructure applied to the world of health care. The course will cover both theoretical foundations and practical applications of these topics, with a focus on the integration of data science techniques with data infrastructure. The course will include hands-on examples from real world data sets the will enhance skills and experiences in health care. In addition to reviewing key steps in the data science process (i.e. data preparation, exploratory data analysis, feature engineering, model selection, model evaluation, and model deployment) and machine learning techniques, we'll explore how to use, apply, and deploy them in various healthcare settings. Students will learn about data architectures, distributed data processing systems, data pipelines, data transformation, and data visualization tools, and how different healthcare players are solving data challenges at scale. By the end of the course, students will have developed a deeper understanding of data science, machine learning, and data infrastructure, and will be able to apply these concepts to solve complex problems in a variety of healthcare domains across a multitude of data types.
• QST BA 880: People Analytics
  This course focuses on developments in People Analytics, an evolving data-driven approach to employee decisions and practices. Managers must decide how to lead people in the context of new technologies, management practices, empirical methods, and increased collaboration with external stakeholders (e.g., software vendors, consultants, academic researchers). The goal of the course is 1) to provide an overview of the people analytics field, 2) to develop skills in research design, and 3) to understand how to implement people analytics projects in an effective and responsible manner. The course covers theory, practice, and methods that are critical for addressing people-related challenges at companies, such as hiring, retaining, evaluating, rewarding performance, and managing teams and social networks, to name a few. While a background in statistics, analytics and regression methods is helpful, it is not required for success in the course. 3 cr.
• QST BA 881: Analytics for Customer Strategies
  In this course, students learn the principal methods of analytics used to maximize customer profitability. They learn statistical tools to identify, target, acquire and develop profitable customers for the long term. Using a rich range of cases drawn from B2C and B2B companies, emphasis is placed on drawing insights from the analyses to inform business strategy. Students will learn to solve core marketing challenges using analytics including measuring demand, defining customer segments, targeting customers for acquisition, and developing customers for profitability.
• QST BA 882: Deploying Analytics Pipelines
  Prerequisites: QSTBA 600, QSTBA 602, QSTBA 780, QSTBA 810, QSTBA 820. This course will equip students with the essential skills for transitioning data analysis and machine learning tasks to the cloud, supporting production workloads. It covers the creation and deployment of data and ML pipelines, including those for generative AI applications, with a focus on data integration strategies, cloud data warehousing, BI, and ML-Ops. Leveraging prior coursework in data management and machine learning, students will learn to implement ETL/ELT processes, monitor data quality, and deploy models as APIs using cloud services.
• QST BA 885: Advanced Analytics 2
  This course covers analytics topics in applied optimization (or prescriptive analytics). In contrast to the unsupervised and supervised machine learning studied in BA820 and BA810 (and BA865) where the focus was to discover patterns and predict uncertain events, this course focuses on determining the best course of action given an objective and a set of constraints. In other words, making operational and strategic decisions using a rigorous and principled approach. The methods learned in this course have broad application including in logistics, marketing, health care, finance, and more. Example problems include determining which products to advertise to which customer to maximize sales, identifying best location of warehouses to best serve geographically dispersed stores or customers, and allocating medical resources to health care facilities to minimize the fallout during an active pandemic. Topics include linear programming, integer programming, network models, and related methods. Students will learn how to set up such optimization problems and solve them using spreadsheets and Python.
• QST BA 888: Capstone Project
  The capstone project course will allow students to work on a data project in a team setting. The goal is for the students to solve a real-world problem using the knowledge, tools, and techniques acquired throughout the program and show their skills to potential employers. This course spans across the degree program and requires multi-semester efforts, however, the vast majority of the work will be done during the spring semester. The final product will be presented to a faculty panel at the end of the spring semester, followed by a poster session which will be open to the public.
• QST BA 890: Analytics Practicum
  The analytics practicum provides an opportunity for students to gain individual, practical experience related to business analytics. Students will complete a report based on one of the following: - Reflection paper related to an internship experience: Students will describe work accomplished and knowledge gained from working on a part-time or full-time internship in an area directly related to Business Analytics (e.g., data engineering, data analysis, data modeling, machine learning, data visualization). The paper should demonstrate the student's knowledge of Business Analytics concepts acquired through the internship experience. - Research Project: Students will select a topic related to Business Analytics which has not been covered in existing coursework or significantly extends concepts taught in the MSBA curriculum. The research topic can be novel or can be an extension of work completed during the capstone project. It should be substantive enough in terms of technical, quantitative, data management, or programming aspects and contain appropriate references. Students should not merely compile work of others, but also display genuine critical thinking.
• QST BA 891: Analytics Practicum 2
  0 cr. The analytics practicum provides an opportunity for students to gain individual, practical experience related to business analytics. BA891 is a required course for all MSBA students on the 16-month track that provides additional opportunity for students to explore new topics or deepen their knowledge and skills, in areas covered in prior coursework (for example, in BA888 or BA890). Students will complete a report based either on a reflection paper related to an internship experience, or on a research project based on a topic related to Business Analytics which has not been covered in existing coursework or significantly extends concepts taught in the MSBA curriculum. The research topic can be novel or can be an extension of work completed during the capstone project or during BA890. It should be substantive enough in terms of technical, quantitative, data management, or programming aspects and contain appropriate references. Students should not merely compile work of others, but also display genuine critical thinking.
• QST BE 101: Introductory Microeconomics for Business and Strategy
  Questrom BSBA first-year students only. Students must choose either QSTBE 101 or CASEC 101. Students cannot take both BE101 and EC101. Business economics provides students with an intellectual framework for understanding how businesses work: how firms interact in markets, and how markets respond to regulation and policy. Business economics has a dual mission: it is both a social science that describes how markets function and a framework that provides practical guidance for business leaders. This course focuses on business-relevant questions of how markets and businesses interact to create and distribute value. The course takes a data-based, empirical approach to these questions and uses experiential learning and interactive activities to enhance students' applications of economics to BU business problems. The course describes how social value is created via innovation and economic growth and how social value can be destroyed through harmful externalities. Effective Fall 2024, this course fulfills a single unit in each of the following BU Hub areas: Critical Thinking, Ethical Reasoning, Social Inquiry 1.
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  • Critical Thinking
  • Ethical Reasoning
  • Social Inquiry I
• QST BE 102: Introduction to Macroeconomics for Business
  Prerequisite: CASEC 101 or QSTBE 101. Questrom BSBA students only. - Sound business decision-making requires an understanding of the economic environment in which firms operate. It requires an understanding of key economic indicators, the role of economic institutions, and the mechanics of the macroeconomy. This course builds upon the Business Economics course in Introductory Microeconomic for Business to introduce students to the economic theories and tools that enable a better understanding of national economic performance; the problems of recession, unemployment, and inflation; money creation, government spending, and taxation; economic policies for full employment and price stability; and international trade and payments, interpreted through the lens of business. The course takes a data-based, empirical approach to these questions and uses experiential learning and interactive activities to enhance students' applications of macroeconomics to business problems. Effective Spring 2026, this course fulfills a single unit in each of the following BU Hub areas: Global Citizenship and Intercultural Literacy, Social Inquiry I.
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  • Global Citizenship and Intercultural Literacy
  • Social Inquiry I
• QST BE 325: Strategy in the Health and Life Science Sector
  Undergraduate Pre-requisite: Sophomore standing. - This course examines the distinctive strategic and economic challenges that healthcare and life science firms face. It explores how innovators, providers, and insurers in the healthcare industry create and capture value. We will develop frameworks of competition specific to the healthcare industry. Public policy responds to the unique features of these markets, and we will examine how this generates new affects business opportunities. The course offers insights into the unique aspects of the U.S. healthcare system and how it compares globally. We explore questions such as: How does payment affect the types of drugs firms develop? How do insurers avoid expensive customers? Who is incentivized to offer high-quality health care? Effective Fall 2024, this course fulfills a single unit in the following BU Hub area: Social Inquiry II.
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  • Social Inquiry II
• QST BE 350: The Psychology of Decision Making: Implications for Business and Public Policy
  Undergraduate Pre-requisite: Sophomore standing. - We provide an introduction to how individuals make decisions, applying the tools of psychology and economics. We will learn to identify common mistakes and biases. Students will have the opportunity to evaluate their own decision- making ability and learn how to make improved decisions. We link each aspect of decision-making studied to current personal finance decision, business problem & public policy issue. This course will improve negotiation ability and prepare students to use social science data to support decisions. The course consists of cases, discussions, lectures & project. Effective Fall 2024, this course fulfills a single unit in each of the following BU Hub areas: Social Inquiry II, Critical Thinking.
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  • Critical Thinking
  • Social Inquiry II
• QST BE 720: Organizations, Markets, and Society
  Understanding and analyzing the core strategic decisions facing businesses in competitive markets. Students will examine how businesses achieve their fundamental goals given the need to produce goods and services efficiently and a market environment reflecting consumer preferences (demand) and the strategies and strengths of competitors. Students will develop analytic skills necessary for understanding core business models and how different models create value for the business as well as the larger society.
• QST BE 721: Economics and Management Decisions
  Graduate Pre-requisite: QST MO712 or MO713 (QST QM716 or QM717 recommended). The aim of the course is to present many of the decision problems managers face and to present the economic analysis they need to guide these decisions. Microeconomic tools are used to structure complicated decision problems about production, pricing, investment, and other strategic issues, address uncertainty through probabilistic forecasts and sequential decisions. An important part of the course is to develop an understanding of the external environment in which firms operate by analyzing the implications of market structure, macroeconomic developments and policy, and other forms of public policy toward business.
• QST BE 834: Macroeconomics in the Global Environment
  Macroeconomics is the study of the aggregate behavior of global market participants, i.e., consumers, firms, workers, governments, central banks, foreign investors. Decision making by investment bankers, product/sales managers, policy makers, or consumers inevitably rely on an understanding of the main forces driving GDP, inflation, unemployment, interest rates, and exchange rates. Consider these questions: 1. Should new consumer durable products be launched during recessions? 2. Are countries that experience high productivity growth good investment targets? 3. Will interest rates drop if the US government starts buying back its debt? 4. With significant liquidity demands by the US economy from the public sector, the household sector and businesses, what explains the low US interest rates? Are these factors expected to keep interest rates low also in the future? 5. Can the Euro boost productivity in Europe in the medium to long run and what are the competitiveness challenges for US businesses of such changes? 6. What are the economic effects of wars and how should they be financed? These and other issues will come up in the course. The main goal of this course is to provide a coherent framework that you can use to understand economic events as you confront them in your work environment.
• QST BE 845: Improving Your Decisions
  The main aim of Improving Your Decisions is to present many of the decision problems managers face and to identify the most effective ways to make sound decisions - as well as the pitfalls, biases, and mistakes that should be avoided. A key element of the course is to present students with a series of decision challenges: What would you do? In other words, you must come to grips with actual decisions and defend your actions. The assigned readings also convey the most recent research findings in behavioral economics: how individuals and managers actually make decisions. The second half of the course centers on group decision making: how groups with common and not-so-common interests decide. The focus shifts from individual choices to group decisions that embody both competitive and cooperative elements.