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

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

Autumn 2026

IMT 598 B: Professional Skills in IM

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

Topic: TBD

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 G: Generative AI Ethics

• Instructor: Belen Saldias
• Credits: 4
• Grading: Standard / 0.0-4.0
• Modality: In-Person

This special topic course will engage deeply with the opportunities and challenges associated with generative AI systems. Generative AI systems have been rapidly proliferating and are now widely used by the public, students, researchers, and developers. While they offer practical human–AI interaction settings, their societal impact 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. 

Summer 2026

IMT 598 A/B: Reading Seminar 

• Instructor: Belen Saldias
• Credits: 2
• Grading: Standard / 0.0-4.0
• Modality: Hybrid

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 spring quarter book will be Duhigg, Charles, Supercommunicators: How to Unlock the Secret Language of Connection.

More about the MSIM Reading Seminar and Community Books. 

Spring 2026

IMT 598B: Cloud Computing and AI: Tools, Services, and Applications

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

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. Students will explore the transition from on-premises systems to cloud-based infrastructure, emphasizing AI-driven applications and services. They will learn about cloud deployment and service models—including public, private, hybrid, SaaS, PaaS, and IaaS—with a focus on their roles in supporting AI development. Students will gain insights into commonly used cloud services such as Virtual Machines, Virtual Networks/Subnets, Web Apps, Databases, Containers, Serverless computing, and AI services. The course also enhances understanding of foundational infrastructure concepts and systems design principles such as load balancing, scalability, reliability, performance, security, and privacy.

Students will delve into the tools, frameworks, and infrastructure provided by leading cloud providers for building, training, deploying, and using machine learning and AI models efficiently. They will 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 the overhead of first training, building, or deploying a model. By the end of the course, students will have a comprehensive understanding of core cloud computing and AI services, empowering them to create scalable, intelligent, and innovative solutions that drive business transformation.

IMT 598D: Advanced Leadership Seminar 

• Instructor: Sean McGann
• Credits: 3
• Grading: Credit / No-Credit
• Modality: Online synchronous
• Prerequisites: IMT 580
• Application Required: Fill out this form when you register

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.  

IMT 598 F/H: Reading Seminar

• Instructor: David Hendry
• 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 spring quarter book will be Allison Pugh, The Last Human Job: The Work of Connecting in a Disconnected World.

More about the MSIM Reading Seminar and Community Books. 

IMT 598 G: Professional Skills in IM

• Instructor: Julie Averill
• Credits: 2
• Grading: Standard / 0.0-4.0
• Modality: In-Person

Topic: Leading Transition

A 10-week, discussion-driven seminar examining transformation through lived leadership stories and  company case studies. Each week explores 1-2 different companies to understand their approach to transformation, successes, failures and learnings . Students prepare short reflections and engage in class discussion.

IMT 598 J: Responsible AI

• Instructor: Mike Teodorescu
• Credits: 3
• Grading: Standard / 0.0-4.0
• 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. 

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

This course is focused on the intellectual foundations of critical engagement with AI. The course will draw on historical, philosophical, and cultural scholarship on information, science, and technology with particular attention paid to disciplinary and epistemological tensions between different modes of knowledge production. Example course topics will cover (but are not limited to): the rise of statistical reasoning and datafied ways of knowing, histories of social surveillance and risk management, and contemporary legacies of relevant prior scientific paradigms (e.g., eugenics, cybernetics, and beyond). Through intensive reading and discussion, students will learn to critically assess the aims and assumptions of various scientific rationalities and cultural logics underwriting AI, demonstrating their learning through 1) an original scholarly essay and 2) a focused study of a prominent AI system or initiative. 

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 MSIM Reading Seminar and Community Books. 

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.