Information Systems

• QST BA 510: Neural Networks and AI: From Foundations to Generative Models
  Undergraduate pre-requisite - QSTBA 222 or QSTBA 223 - This course will introduce students to neural networks, from the most basic formulations through contemporary generative AI architectures. Students will learn to implement NNs with various types of structured and unstructured data (e.g., images, text, video, audio) employing TensorFlow and Keras.
• QST BA 576: Machine Learning for Business Analytics
  Undergraduate Prerequisites: CAS CS108 or CAS CS111 or CDS DS110 or QST BA222 - Formerly BA476. 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 HM 817: Advances in Digital Health
  Graduate Prerequisites: QST HM710 or HM717 - Digital technologies are fundamentally transforming the health sector. Health information technology now permeate every segment of the health value chain, starting with the search for health information, to improving patient outcomes, to improving health. In this course students explore the evolving digital health landscape through a mix of case studies, practitioner talks, individual papers and team projects. Students will enhance their digital health requirements and systems selection toolbox. They will develop competence in current digital health technology standards, gain a deeper understanding of the strategic drivers of digital health through the eyes of the healthcare CIO and CMIO, the operational challenges from the perspective of the end user and the healthcare providers, and challenges of incorporating digital health technologies into existing workflows.
• QST HM 840: Health Sector Consulting
  This is an applied consulting project course that aims to develop reflexive practitioners who can elicit client requirements, translate requirements into a problem statement and develop actionable solutions that meet client needs. The course uses a mix of case studies, individual memos and team project deliverables to systematically apply skills developed over the course of the MBA to solve real-world health sector problems. Students work on the consulting assignment in teams of up to four students based on having a shared interest in a prospective consulting project. These projects are curated in partnership with sponsor organizations to be executable within the framework of an academic semester. Projects in the past have ranged from improving the departmental revenue cycle within an academic medical center, developing an international pricing strategy for the introduction of a new product by a pharmaceutical company, to improving safety culture at a large hospital. These projects all have active involvement of the project sponsors who provide access to their organizations and provide ongoing feedback over the lifecycle of the consulting engagement.
• QST IS 223: Information Systems and Emerging Technologies in Business
  Undergraduate Prerequisite: QSTSM 131 - Provides students with an understanding of the important role that information and information technology play in supporting the effective operation and management of business. The course highlights issues in managing information systems for competitive enterprises and the nature of competition in digital markets. Further, the course introduces modern business technologies, including generative artificial intelligence and supports the application of these tools to real-world business projects.
• QST IS 428: Managing Information Security
  Undergraduate Prerequisites: (QSTIS223) - Combines technical and business approaches to the management of information. It will address technical issues such as cryptography, intrusion detection, and firewalls along with managerial ideas such as overall security policies, managing uncertainty and risk, and organization factors. We will examine different aspects of computer security such as password, virus protection, and managing computer security in dynamic environments. Topics will also include network security and how to secure wireless application and services. These technical details will be placed in a business context. The class will have a practical focus as we examine current "best practices" in area. There will be several guest speakers in the security area. This will be a project-oriented class and students will present their research projects during the last several classes. 4 cr.
• QST IS 467: Agile Development Methodologies
  Undergraduate pre-requisite: QSTIS 223, and pre-requisite or co-requisite: QSTBA 222 or CASCS 105 or CASCS 108 or CASCS 111 or CDSDS 110 - This course is designed to provide the students with an overview of Agile Development methodologies. The course introduces the various methods currently used in the industry and then focuses on the primary methodologies used today, SCRUM and Kanban. Students will learn the tools of these software development approaches that produce deliverables to end users every two to four weeks. We analyze the value each of these methodologies bring into the development process and the reasoning behind a corporation selecting one method over the other (or a combination of both). In addition, the students will be introduced to CA Project Management software, the leader in the industry for SCRUM. Students will learn to analyze requirements, create backlogs, schedule "stories" to be developed, hold Standup meetings, Reviews and Retrospectives.
• QST IS 469: Designing Information Systems
  Undergraduate Prerequisites: (QSTIS223) - Studies the process of designing and implementing management information systems. Students will learn to analyze organizational information requirements, develop specifications for information systems, manage systems development projects, and understand implementation issues. Key implementation concepts that affect management decisions will be discussed, and reinforced with programming examples. Design support tools will be used to support the design process. Includes a project to design an information system.
• QST IS 474: Platform Strategy & Design
  Undergraduate Prerequisites: (QSTIS223) - Today's most valuable and powerful companies do not offer standalone products or services, but rather platforms which enable transactions between multiple customer groups -- think Alibaba, Airbnb, Amazon, eBay, Facebook, Google, Microsoft, Salesforce, Uber, etc. This course explores the unique strategy challenges and economic foundations of such platform businesses. What makes platforms special relative to regular product businesses' Why are platforms so powerful, yet so hard to build' How should platforms be designed and priced' How much responsibility should platforms take for bad things they enable their participants to do (e.g. fake news and ad scams on Facebook, counterfeits on Alibaba)' When and how can regular products or services be transformed into platforms' How should other businesses deal with the rising power of platforms that they depend on' The course will use a mixture of conceptual frameworks, (light) economic models, and case studies to provide students with a thorough and in-depth understanding of what it takes to build or invest in platforms. Such an understanding is indispensable to anyone seeking a career at technology companies or aspiring to become an entrepreneur or venture capitalist.
• QST IS 498: Directed Study: Management Information Systems
  Directed study in Management Information Systems. 2 or 4 cr. Application available on Undergraduate Program website.
• QST IS 565: Managing Data Resources
  Undergraduate Prerequisites: QST IS223 and QST BA222 or CAS CS105 or CAS CS108 or CAS CS111 or CDS DS110 (co-requisite /pre-requisite) - Required for Information Systems concentrators. Provides a practical and theoretical introduction to data management focusing on the use of relational database technology and SQL to manage an organization's data and information. Introduces recent topics such as data warehouses and Web databases. Includes a project to design and implement a relational database to manage an organization's data. 4 cr.
• QST IS 579: Financial Business Modeling with Spreadsheets
  Prerequisites: QSTAC414 or QSTAC420 or QSTFE445 or QSTFE449 or QSTIS465 or QSTSI445 This course enhances students' quantitative modeling and analysis skills in addressing complex financial decisions, focusing on effective problem formulation and analysis. Students will learn to identify the critical components of the decision-making tasks, structure them methodically, translate them into visual and analytical models, and develop appropriate mathematical models and their spreadsheet solutions. With a focus on finance modeling, the course introduces advanced Excel tools, such as Pivot Tables for interactive data analysis and Power BI for building executive KPI dashboards. Students will explore essential data management and decision tools such as Formula Diagrams, Linear Optimization, Error Detection methodologies, and Parametric Sensitivity Analysis. The course also provides extensive hands-on experience with Solver to optimize financial strategies, such as designing an investment portfolio that optimally balances risk and return. Real-world applications drawn from finance and accounting will guide students through the financial modeling cycle: planning, control, and feedback. By the end of the course, students will have developed the technical and analytical skills needed to approach complex financial problems and deliver data-driven solutions that support thoughtful strategic decision-making.
• QST IS 717: Systems Architecture in Management and Applications
  Graduate Prerequisites: MSDT students only - The objective of this course is to provide an overview of the concept of systems architecture and how it has evolved from a technical notion to an important business issue. The course has several themes: (1) Students develop an appreciation of how a business may leverage architectural design choices for operational and competitive advantage, both at a technical and business level. (2) Students obtain insight into how interface driven systems (those using APIs) enable flexibility and increased innovation. (3) Students are confronted with the difficult aspects of modern systems, such as parallelism and concurrency, and how these technical challenges are managed. An introduction to programming in Python provides a context to help students develop a hands-on understanding of these concepts. Care is taken to not just apply the technical material to management contexts, but also inform business strategy and organization and operations through these architectural principles.
• QST IS 737: Decision Making with Data
  Graduate Prerequisites: QST IS717, IS833, IS834, QM877, or knowledge of Python - This is an advanced python-based analytics course on data-driven decision-making in business environments. Business analytics professionals need to be able to i) uncover patterns in the data (descriptive analytics); ii) use the data to make predictions about future outcomes (predictive analytics); and iii) leverage this data to make optimal business decisions (prescriptive analytics). This course takes a holistic approach to analytics, touching on aspects of all three descriptive, predictive, and prescriptive pillars. We explore advanced business analytics topics, including data reduction, classification, decision analysis, and optimization. We link data models to strategy relying on statistical programming in Python and introduce novel techniques used in practice. Case studies and projects apply topics to practical business problems. 3 cr.
• QST IS 795: Blockchains and their Applications
  Blockchain technology amalgamates technical tools, economic mechanisms, and system design patterns. It facilitates the construction of information systems with novel combinations of robustness, decentralization, privacy, cost, and flexibility. Beyond their initial use in cryptocurrencies such as Bitcoin, blockchains have become a promising and powerful technology in business, financial services, law, and other areas. This course covers blockchain technology in a comprehensive, systematic, and interdisciplinary way. It surveys major approaches, variants, and applications of blockchains in these areas. Beyond a solid grasp of the principles, the course aims to build familiarity with practice through numerous case studies and hands-on projects. To facilitate its interdisciplinary perspective, this course will be open to two categories of students: students with Computer Science background (graduate or advanced undergraduate), and graduate students with a substantial Business or Law background and a working knowledge of computer programming. Projects will be done in heterogeneous teams combining these categories, and will center on devising and analyzing sample applications of blockchain technology, including both prototype implementations and analysis of its business/legal implications. Topics covered: disentangling ¿blockchain¿; cryptographic prerequisites; assets and their representations; on-chain programming; state consensus; deployments; decentralized applications (Dapps/Web3); protocol governance; protocol revenue and business models; market structure; privacy and authorization; regulation.
• QST IS 811: Responsible AI for Business Analytics
  AI and data are powerful tools that require thoughtful and responsible applications. The stakes are high as algorithms can scale to influence millions and even billions of people within a moment of launch and morph businesses and society with the impact that might last generations. Our mission is to understand and anticipate potential pitfalls and misuse of personal data and AI to guard against harm. We will also discuss existing solutions and the lack of solutions. The course is designed to be accessible to everyone and targeted to practitioners whose businesses will use some form of data and algorithms. Examples from Technology, Retail, Marketing, Health Care, Finance, and Society will be discussed.
• QST IS 813: Generative AI: Implementation and Impact for Business
  Central to the curriculum is the practical, hands-on approach to understanding Generative AI. Students will gain firsthand experience with language models like GPT, learning the intricacies of model fine-tuning, prompt engineering and its various frameworks, and deployment strategies through interactive sessions and real-world projects. This approach ensures that participants develop a robust technical skillset, enabling them to effectively implement and utilize Generative AI technologies in business contexts. The course also delves into advanced issues critical to the responsible implementation of AI including privacy, ethics, bias, data integrity, and challenges like mitigating hallucinations in AI outputs. By the end of the course, participants will be equipped not just with theoretical knowledge but also with practical skills, empowering them to harness the potential of Generative AI in innovative and strategic ways. While some minimal coding experience is expected, this class does not require advanced technical skills as a pre-requisite.
• QST IS 823: Analytics for Managers
  This non-programming-based analytics course examines how the abundance of data has transformed decision making in organizations and the strategic implications of this transformation. We explore how data are being used, ranging from the core principles of properly identifying data sources to the actual analytical methods being used to solve a wide range of business problems. Students will have some hands-on work with advanced Excel, Tableau, and two database applications, Microsoft Access and Neo4j (Neo4j is used to compare and contrast SQL and NoSQL databases in an analytics context). At the end of this course, students will have gained a big-picture perspective on business analytics as well as hands-on experience with commonly-used business analytics software.
• QST IS 827: Platform Strategy and Design
  Graduate Prerequisites: QST PL727 or PL730, QST SI750 or SI751, or permission of instructor - To thrive in the modern economy, managers, entrepreneurs and investors need a thorough understanding of platform businesses. Indeed, today's most powerful and valuable firms, from Airbnb, to Amazon, Facebook and Salesforce, operate as platforms connecting buyers and sellers, or users and advertisers, or users and third-party developers. These platforms derive their value from network effects and the ability to harness innovation from their users. Drawing on cases from social media, entrepreneurship, enterprise software, mobile services, and consumer products, we will analyze and learn to launch platform startups, convert existing businesses into platforms, and compete in a platform-centric world. Students will learn to apply concepts from industrial economics, market design, and game theory to real problems.
• QST IS 828: Managing Information Security
  Graduate Prerequisites: IS710/711/716 - This MBA elective (also open to undergraduates) will combine a technical and business approach to the management of information. It will address technical issues such as cryptography, intrusion detection and firewalls along with managerial ideas such as overall security policies, managing uncertainty and risk and organization factors. We will examine different aspects of computer security such as passwords, virus protection and managing computer security in dynamic environments. Topics will also include network security and how to secure wireless application and services. These technical details will be placed in a business context. The class will have a practical focus as we examine current best practices. There well be several guest speakers in the security area. This will be a project oriented class and students will present their research projects during the last several classes.