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View special topics and new courses for other Information School programs:

• MLIS courses (LIS)
• Ph.D. courses (INSC)

Winter 2026

IMT 598 A: Qualitative Design Methods for Data Science

• Instructor: Jaime Snyder
• Credits: 4
• Grading: Standard / 0.0-4.0
• Modality: In-Person

Data science students are introduced to qualitative and design methods to support human-centered perspectives, heighten awareness of discriminatory practices, and make connections between identity and data. Readings and hands-on activities provide students with novel tools for better understanding the ways in which people are defined and represented through data practices.

IMT 598 D: Epistemological Foundations of AI

• Instructor: Bill Howe
• Credits: 3
• Grading: Standard / 0.0-4.0
• Modality: In-Person

Description coming soon.

IMT 598 E: Low-Code / No-Code Development

• Instructor: Fawad Khan
• Credits: 4
• Grading: Standard / 0.0-4.0
• Modality: In-Person

According to Gartner, 70% of new applications developed by enterprises in 2025 will use low-code or no-code technologies, up from less than 25% in 2020. Learn about the next revolution in cloud application development using low-code and no-code platforms. Discover how regular IT professionals and business users can solve common and complex business problems by building applications with minimal or no development experience using these platforms. Many modern low-code/no-code platforms now leverage AI to automate code creation, perform architectural reviews, conduct testing, and manage deployment. In this course, we will explore and use some of these key tools, build applications, and understand how product development and management are evolving in today's digital age. Finally, you will learn how to harness the power of data to quickly build business and personal solutions by integrating data from various sources, incorporating business workflows, building internal and external websites, and embedding virtual chatbots into your applications.

IMT 598 F/I: Reading Seminar

• Instructor: Heather Whiteman
• Credits: 2
• Grading: Credit / No-Credit
• Modality: Online Synchronous

In this quarterly reading seminar, you will read about 60-90 pages per week and discuss a text at one weekly meeting. You will develop your thinking and leadership skills while helping to create a flourishing community of information management professionals. The Winter 2026 book: Suzman, J. (2020). Work: A Deep History, From the Stone Age to the Age of Robots.  New York: Penguin Books.

More about the . 

IMT 598 G: Professional Skills in IM

• Instructor: Heather Whiteman
• Credits: 2
• Grading: Standard / 0.0-4.0
• Modality: In-Person

Winter quarter 2026 Professional Skills in Information Management Seminar focuses on developing the ability to analyze qualitative data. Students will gain practical experience in organizing, coding, and interpreting non-numerical data to uncover patterns, themes, and insights. The seminar will equip students with strategies and tools for turning unstructured data—such as interviews, focus groups, and open-ended survey responses—into actionable knowledge for decision-making. 

IMT 598 J: Implementing and Managing AI

• Instructor: Richard Sturman
• Credits: 4
• Grading: Standard / 0.0-4.0
• Modality: In-Person

This course explores the strategies and considerations needed for the effective deployment, governance, and management of AI systems within organizational settings. Students will examine the ethical implications of AI and the importance of ensuring that these systems serve the needs of diverse populations and organizational goals. Students will learn how to design and implement AI systems that align with organizational objectives while prioritizing human well-being, fairness and sustainability, through real-world applications, case studies, and hands-on projects.

Autumn 2025

IMT 598 A: Generative AI Ethics

• Instructor: Belén Saldías Fuentes
• 4 credits; standard grading 

This special topic course will delve into the opportunities and challenges associated with generative AI systems. Generative AI systems have been rapidly proliferating and are widely used by laypeople, students, researchers, and developers. While they offer practical human-AI interaction settings, their impact on society remains poorly understood. 

Through readings, discussions, scaffolded hands-on technical probing of models, and research-focused projects, students will explore and challenge how to responsibly design, use, develop, and deploy generative AI systems while raising awareness about the numerous open questions that are critically important to the sciences and society. By the end of the course, students will be better positioned to contribute to the discussion and technical advancements needed for responsible and sustainable AI progress. This course is designed for students with diverse backgrounds, ranging from the social sciences to computer and information sciences. Projects will range from literature review to data collection and analysis to user studies to model training or prompting for new tasks evaluation.

IMT 598 B: Foundations of Entrepreneurship

• Instructor: Mike Teodorescu
• 4 credits; standard grading 

This course will create a welcoming environment for students of all degrees to learn about the fundamentals of starting a new business, venture capital, developing intellectual property, and writing a business plan. The theoretical foundations will draw from the management, economics of innovation, and entrepreneurial finance literature. The course will rapidly develop skills needed to think about building a business, such as defining a problem area, finding a market, feasibility analysis of proof of concept, IP considerations, and finally how to pitch for funding. The course will conclude with group projects where students develop a business idea proposal and will pitch it to a panel of judges for feedback, as in traditional startup accelerators. External judges such as angels, business faculty, or venture capitalists will be invited for the event by the instructor to provide diverse viewpoints and feedback for the business plan proposals.

IMT 598 C: Digital Transformation in the Age of AI

• Instructor: Fawad Khan
• 3 credits; standard grading 

This course explores the fundamentals of Digital Transformation and the emerging technologies driving change across industries. Students will examine how organizations are leveraging digital strategies to enhance competitiveness, operational efficiency, and customer value.

Topics include the core pillars of digital transformation and an in-depth look at enabling technologies such as Cloud Computing, Machine Learning, and Artificial Intelligence (AI). The course also covers advanced AI concepts, including Large Language Models (LLMs), Generative AI, and AI agents. Emphasis will be placed on how these technologies are reshaping the IT landscape and their implications for the future of work and innovation.

IMT 598 D and G: Reading Seminar in Information Leadership

• Instructor: David Hendry
• 2 credits; standard grading 

Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the new Frontier of Power. New York: Public Affairs. [978-1610395694] [About $20.00 at the usual places] []

Shoshana Zuboff develops seven different definitions of “surveillance capitalism,” the first being “a new economic order that claims human experience as free raw material for hidden commercial practices of extraction, prediction, and sales.” In this reading seminar, we will study this and the other six definitions and explore the implications for democracy, organizations, professionals in information management, and our children and grandchildren.

About the MSIM Reading Seminar and Community Books:

IMT 598 E: Professional Skills in Information Management

• Instructor: James Lamar Foster
• 2 credits; standard grading 

The Professional Skills in Information Management Seminar gives students an opportunity to develop skills in an essential topic of information management. Examples include: How to plan, run, and analyze data from a SWOT workshop; How to plan, conduct, and analyze data from a set of interviews; How to conduct a stakeholder analysis; How to employ creative methods for strategic envisioning.

IMT 598 I: Foundations of Artificial Intelligence

• Instructor: Chirag Shah
• 4 credits; standard grading
• Online synchronous

AI Foundations equips students with a comprehensive understanding of the technical underpinnings and critical perspectives on artificial intelligence (AI). The course explores the neural architectures, learning methodologies, and computational principles that enable modern AI systems, while critically examining their fundamental capabilities and limitations. Students will engage with interdisciplinary perspectives on AI's societal implications, and its potential impact on organizations and an organization's stakeholders. This includes philosophical questions of intelligence, creative expression, knowledge representation, and human-machine relationships. A significant focus is placed on responsible AI frameworks, including ethical considerations, fairness principles, and mechanisms for ensuring accountability and transparency.

Summer 2025

IMT 589 A/B: Reading Seminar 

• Instructor: David G. Hendry
• 2 credits; Credit/no-credit grading

Herbert Simon won the Nobel Prize in Economics in 1979 for pioneering research into decision-making. The Nobel Prize Committee wrote: “In his epoch-making book, Administrative Behavior (1947), and in a number of subsequent works, he described the company as an adaptive system of physical, personal and social components that are held together by a network of intercommunications and by the willingness of its members to cooperate and to strive towards a common goal” (Nobel Prize Outreach. [2025, April 23]. Nobel Prize Press Release 1978). In this reading seminar we will study and discuss this seminal book and Simon’s insights into how organizations work and how they can be designed to work well.

Simon, H. A. (1997). Administrative Behavior (4th edition). New York: Free Press. [978-0684835822] [About $16.00 at the usual places] [NOTE: PLEASE GET THE 4th EDITION.]

For more about the MSIM Reading Seminar and Community Books:

Spring 2025

IMT 589 A: Cloud Computing and AI: Tools, Services, and Applications

• Instructor: Fawad Khan
• 4 credits; Standard grading

This course introduces the concept of Cloud Computing with a primary focus on how it is revolutionizing the development and deployment of Artificial Intelligence (AI) solutions. Explore the transition from on-premises systems to cloud-based infrastructures, emphasizing AI-driven applications and services. Learn about Cloud Service models, including SaaS, PaaS, and IaaS, with a focus on their role in supporting AI development. Delve into the tools, frameworks, and infrastructure provided by leading cloud providers for building, training, and deploying machine learning and AI models efficiently. Understand how to evaluate cloud services for AI applications based on costs, security, compliance, fault tolerance, and disaster recovery. Gain insights into the most consumed cloud services for deploying and maintaining virtual machine networks and AI-enabled solutions.

Discover how to leverage pre-built APIs and services from major providers, such as OpenAI, to develop intelligent applications utilizing state-of-the-art large language models (LLMs). These include APIs for speech, vision, language understanding, search, knowledge extraction, and translation, enabling rapid development without extensive training or deployment overhead.

By the end of the course, you will have a comprehensive understanding of how to integrate AI and cloud computing technologies to create scalable, intelligent, and innovative solutions that drive business transformation.

IMT 589 D & G: Design Methods for Interactive Systems 

• Instructor: Nicholas Logler
• 4 credits; Standard grading
• Online synchronous

This course examines design methods for identifying and describing user needs, specifying and prototyping new systems, and evaluating the usability of systems. Through a mix of design studios, in-class activities, and projects, students will begin to cultivate a design practice by applying design methodologies such as contextual design, human-centered design, prototyping, and more to complex problems. By the end of the course, students will have started to develop a design sensibility which they can apply to a range of challenges, as well as a basic understanding of the core concepts and principles which contemporary design methods are built upon.     

IMT 589 I: Reading Seminar 

• Instructor: David G. Hendry
• 2 credits; Credit/no-credit grading

Alan Blackwell makes the case that to benefit from artificial intelligence we need to develop better tools, including programming languages. In this reading seminar, we'll read Moral Codes slowly and explore how tools augment human intellect and expand human creativity. And, we'll gain perspective on the possibilities for artificial intelligence.

Blackwell, A. (2024). Moral Codes: Designing Alternatives to AI. Cambridge, MA: MIT Press. [ISBN-13: 978-0-262-54871-7] [About $35.00 at the usual places | UW Library] 

For more on the MSIM Reading Seminar and Community Books, see:

IMT 589 J: Reading Seminar 

• Instructor: David G. Hendry
• 2 credits; Credit/no-credit grading
• Online synchronous

Alan Blackwell makes the case that to benefit from artificial intelligence we need to develop better tools, including programming languages. In this reading seminar, we'll read Moral Codes slowly and explore how tools augment human intellect and expand human creativity. And, we'll gain perspective on the possibilities for artificial intelligence.

Blackwell, A. (2024). Moral Codes: Designing Alternatives to AI. Cambridge, MA: MIT Press. [ISBN-13: 978-0-262-54871-7] [About $35.00 at the usual places | UW Library] 

For more on the MSIM Reading Seminar and Community Books, see:

IMT 589 K: Responsible AI

• Instructor: Mike Teodorescu
• 3 credits; Standard grading
• Recommended preparation: IMT 572 or any 500 series data science course.

Take a course on Responsible AI from one of the pioneering researchers in Information Systems on machine learning fairness! The Responsible AI course is designed for managers, software engineers, consultants, and policy makers interested in the latest regulations, research, methods and standards regarding building responsible AI systems. The Responsible AI course will cover policy documents, such as the US and EU regulations on AI, the concepts of fairness criteria from computer science, testing algorithms for fairness, visualization techniques relevant to fairness such as SHAP and LIME, case studies, and reading and discussing some of the latest research in the space. The hands-on applications during the course will include an R component, similar to IMT 572 and other courses. If you do not have R or Python experience, we will have a refresher as an optional session. 

Deliverables: case study discussions, class reading and discussion, and data analysis and software exercises. There will be no final exam. Opportunity will be given to students with different professional interests to choose the topics of the homework assignments that better suit their interests, while not neglecting the core elements of the discipline.

IMT 589 L & M: Advanced Leadership Seminar 

• Instructor: Sean McGann
• 3 credits; Credit/No-credit grading
• Online synchronous
• Prerequisites: IMT 580
• Application required - Please complete the by the add code distribution dates listed on the form. 

In this seminar, we seek to deepen the skill development started in IMT 580, through continuation of The Leadership Challenge and the Leadership Practices Inventory (LPI). As a class, we will dive more deeply into each of the 5 practices, through discussion and reflection exercises. Through individual coaching sessions, the instructor will examine each student’s LPI, and discuss strengths and areas for improvement, working with them to better understand the results and coaching them on how to develop and implement strategies for long-term leadership development. Students will also leverage peer groups to share, reflect and advise each other on LPI results and leadership development lessons learned.