Special topics courses - Fall 2026

AR & UX for Automotive - J. Weiss

SI 311.017 - 3 Credits - Class Number 28481

This course will introduce you to the world of Augmented Reality (AR) interfaces as applied to the Automotive Environment. These interfaces enable new kinds of automotive user experiences by superimposing digital content onto the driver's real-world view. You will learn about the technical and design requirements for creating such user experiences and how to prototype your AR interfaces. You will learn fundamental application areas such as Safety, Navigation and Situational Awareness through case studies and in-class design exercises. You will learn how to apply different graphical representations to best present AR content to the driver in a meaningful way. You will learn how AR Applications in Automotive are different from other AR Applications. You will learn how to approach technical constraints in interaction design for Automotive AR and how to balance technical limitations. This course is structured into a series of mini-design projects leading up to a final course project that you will develop and implement over several weeks.

Sports Analytics - T. Finholt

SI 311.030 - 1-3 Credits - Class Number 37485

In this course students will work with the instructor and with training/coaching personnel in U-M Athletics to address a set of analyses related to athlete health, safety or performance, such as by using data gathered from: tracking devices worn in practice and competition (e.g., Catapult); cameras (e.g., TrackMan); or boxscore and other statistical data (e.g, Pro Football Focus). These datasets can be large and complex. For example, wearables data typically consist of a hundred records per second with a dozen or so variables per record (e.g., distance traveled, direction of movement, number of explosive movements) – collected longitudinally across up to fifteen athletes per team per season.

Prerequisites: Application required

Students are advised to have completed (or be currently taking) an introductory level stats course (e.g., STATS 250) and an introductory programming course (e.g., EECS 183, ENGR 101/151 or SI 106).

UX-Driven Entrepreneurship - N. Fang

SI 311.085 - 3 Credits - Class Number 28418

Discover the synergy of design thinking and entrepreneurship. This course blends UX methodologies with entrepreneurial strategies by exploring problem-solution scoping through user research & market analysis, and learning business models through a human-centered lens. The course will include hands-on and client-based exercises to transform innovative ideas into pitches for user-centric startups.

Generative AI & UX - J. Rampton

SI 311.151 - 3 Credits - Class Number 28364

A special topics course exploring the potential and perils of Generative AI for UX Research and Design. Students and instructors will explore emerging tools for creating designs and assisting with UX Research, and will critique said tools while also developing a personal statement about the future of UX practice in the AI era.

CXD in Auto Industry - W. Thompson

SI 311.155 - 3 Credits - Class Number 26130

Customer Experience Design: Propelled by digital experience and connected services, the automotive industry is transforming at a historically exponential rate. In this course, we will examine the factors driving this change to identify, design and propose solutions for Cross-Channel experiences in the world of connected vehicles. Students will be asked to evaluate current experiences and identify business and experience trends to discover what brings value to a business and its users. We will learn how to unlock the power of design thinking and apply modern UX business practices to drive meaningful results and drive industry transformation. Upon completion of this course, students will be able to identify and analyze areas of opportunity, create design proposals and present findings using a range of mediums.

Entrepreneurship Studio (GB2) - M. Lee

SI 311.174 - 1.5 Credits - Class Number 37488

In this hands-on studio course, students will run many entrepreneurial experiments with the goal of learning to think entrepreneurially, work through failures and discomfort, and verbally communicate their learnings to others. Students will be placed on teams throughout the studio course to engage in hands-on experiments, case studies, and mini-competitions.

This course runs in the second 7 weeks.

Applied Data Analysis w/ Excel (GB1) - J. Kim

SI 311.175 - 1 Credit - Class Number 37495

The course teaches students practical workflows that analysts commonly use to clean, organize, and analyze data in Excel. Through hands-on exercises, students will learn essential functions, pivot tables, and basic visualization techniques to generate valuable business insights. The course utilizes real-world datasets and emphasizes the importance of data analysis in making informed, data-driven decisions.

This course runs in the first 7 weeks.

Applied Data Analysis w/ Tableau (GB2) - J. Kim

 SI 311.176 - 1 Credit - Class Number 37496

The course introduces students to the workflows analysts use to transform structured data into dynamic, decision-ready dashboards. It focuses on advanced data analysis, modeling, and interactive visualization using Tableau. Students will learn how to combine multiple data sources, create calculated fields, and create dynamic dashboards to facilitate exploration and decision-making.

This course runs in the second 7 weeks.

Research Experience Development Program - K. LaPlant

SI 311.512 - 1.5 Credits - Class Number 33921

This course provides supplemental research training to complement research experiences provided by UMSI researchers. Through a weekly seminar, students will receive instructor and peer support while engaging in their project hosted by a UMSI researcher. Seminar topics will include literature reviews, authorship, ethics, and academic research versus professional research.

This course is by application only; see umsi.info/mcompass.redp for more information.

Entrepreneurship Studio (GB1) - M. Lee

SI 511.058 - 1.5 Credits - Class Number 33716

In this hands-on studio course, students will run many entrepreneurial experiments with the goal of learning to think entrepreneurially, work through failures and discomfort, and verbally communicate their learnings to others. Students will be placed on teams throughout the studio course to engage in hands-on experiments, case studies, and mini-competitions.

This course runs in the first 7 weeks.

Visual Storytelling - J. Cruz

SI 511.073 - 3 Credits - Class Number 27653

Learn how to use visual storytelling to communicate ideas, engage audiences, and inspire action. Through hands-on projects, students explore presentation design, data visualization, branding, social media, and more. Build a portfolio of visual work while developing practical storytelling skills applicable across industries and professions.

Generative AI & UX - J. Rampton

SI 511.151 - 1.5 Credits - Class Number 27654

A special topics course exploring the potential and perils of Generative AI for UX Research and Design. Students and instructors will explore emerging tools for creating designs and assisting with UX Research, and will critique said tools while also developing a personal statement about the future of UX practice in the AI era.

Go-to-Market Strategy and Growth Analytics - S. Manzar

SI 511.176 - 3 Credits - Class Number 38382

Learn how products win markets. Students  build a complete GTM strategy, including market and competitive analysis, target segments, positioning, pricing, channels, and launch strategy. Hands-on labs in GA4, Amplitude, and Mixpanel build skill in growth metrics and market experiments.

Communicating Effectively Building Credibility, Confidence, and Leadership in Organizations - N. Sunstrum

SI 511.204 - 3 Credits - Class Number 38296

Communication shapes how people understand ideas, earn trust, make decisions, and work together. This course develops practical communication skills for organizational life through audience analysis, presentations, executive briefings, meeting facilitation, difficult conversations, case studies, and a capstone simulation. Students practice translating expertise for different audiences, communicating under pressure, and using AI with sound editorial judgment. Major work contributes to a Professional Communication Portfolio that shows growth across the semester.

Behavioral & Humane Design: With Persuasion, Emotion, Trust - S. Brenton

SI 611.108 - 3 Credits - Class Number 30846

This graduate course covers advanced UX design, focusing on persuasive, emotional, and trust-building techniques, humane design principles, and testing design hypotheses. Students will run experiments, redesign a website, and learn to persuade stakeholders that their designs enhance user experience while meeting common real-world business goals.

This course has an enforced prerequisite of SI 582 or waiver.

Designing Human-AI Interaction - M. Kyung Lee

SI 611.177 - 3 Credits - Class Number 38341

As AI becomes increasingly integrated into digital products and services, designers must consider how to create human-centered experiences that effectively combine human and AI capabilities. Designing these systems requires more than building interfaces around AI models. It requires understanding when and how AI can add value, how people and AI should work together, and how these systems affect the people and communities who use or are affected by them.

This course has an enforced prerequisite of SI 582 or waiver.