Special topics courses

Tentative Winter 2025 Offerings

Undergraduate Courses

AR & UX for Automotive - J. Weiss (SI 311.017 - 3 credits)

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.

Introduction to Accessibility - T. McCarley (SI 311.026 - 3 credits)

This class will focus on how to think about disability in the context of design and socio-technical systems. Most accessibility content focuses on web accessibility for people who are blind or low vision. While this will be one component of the class, you will learn how to design for people with disabilities (e.g. hearing loss, cognitive decline, etc.) online and offline; how to design for visible and invisible disabilities; and how to design for permanent, situational, and temporary disabilities.

Data Visualization - R. Vergel (SI 311.037 - 3 credits)

In an increasingly data-driven world, the ability to visualize data is critical. This course introduces the principles of data visualization, focusing on the Block Model. Through a series of hands-on exercises, students will be able to understand how to map visualization tasks on some useful abstraction, and then how to encode this abstraction by using the Grammar of Graphics, to create intuitive algorithms on Python to visualize data, using graphical representations. Python is one of the essential languages required in data science. Many data visualization libraries in Python are built to perform numerous functions, contain tools, and have methods to manage and analyze data. However, we do not just learn how to use tools, but we will explore some of the best practices when you need to create effective data visualizations.

SQL & Databases - M. Hess (SI 311.050 - 3 credits OR SI 311.049 - 1.5 credits)

This course will introduce the students to beginning and intermediate database concepts to prepare the student to use databases as part of a data analysis workflow. The students will learn data modeling, SQL Syntax, understanding how to evaluate different database systems for suitability, how to evaluate and improve the performance of database operations, how to use a database in a multi-step analysis process.

Product Design - Z. Razzacki (SI 311.051 - 3 credits)

Have you ever wondered how some of the world's most innovative companies come up with exciting new product ideas? This course offers a unique, hands-on experience for students eager to explore the interplay between business, design, and engineering in product innovation. Taught by industry experts and leaders, it provides a comprehensive look at how to identify market opportunities, develop a product vision, and bring innovative products to life through iterative cycles of experimentation and learning. Key learning outcomes include:

Applying tools and frameworks of product strategy, such as the Business Model Canvas and Value Proposition Canvas, to assess desirability, viability, and feasibility (DVF) of new products concepts.
Learning to collaborate across disciplines, understanding how design, engineering, and business must integrate for successful product innovation.
Building and testing prototypes, conducting experiments, and learning to validate product-market fit through data-driven insights.
Developing and delivering compelling product pitches that synthesize market research, user insights, and strategic vision.

This class is well suited for students from diverse academic backgrounds—especially those in business, design, and engineering—who aspire to leadership career paths at product-led companies or launching their own entrepreneurial start-up ventures. By blending theory with real-world application, students have an opportunity to gain the skills to confidently lead new product initiatives from ideation to market success.

Seminars in Organizational Studies (311.069 - 1 credit)

This seminar provides a forum for the discussion of research and theory about organizations and organizational processes. In keeping with its interdisciplinary character, the seminar will consider both macro and micro-processes and their intersection. Presentations will be made by faculty and advanced graduate students from within the university, as well as from other universities and centers for research on organizations.

Note: Requires senior standing

UX-Driven Entrepreneurship - N. Fang (SI 311.085 - 3 credits)

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.

AI for Problem Solving - J. Zhou (SI 311.125 - 3 credits)

Students will learn how to use commercial AI tools to solve information problems, including how to engineer prompts to elicit the most value from these tools. Additionally, students will learn about some of the underlying logics of these tools and how they affect the abilities of these tools to solve problems.

Machine Learning - K. Srinivasan (311.136 - 3 credits)

This course provides a practical introduction to machine learning using Python, focusing on essential libraries like pandas and scikit-learn. Students will learn a clear, step-by-step approach to building machine learning models and explore popular and effective techniques for methods for classification, regression, and clustering. Through assignments built around analyzing real datasets, students will gain hands-on experience applying these methods to solve pragmatic problems. This course is ideal for students looking for an introduction to how machine learning methods can be applied across a range of disciplines.

Note: Requires senior standing

Generative AI + UX - J. Rampton (SI 311.151- 1.5 credits)

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 the Automotive Industry - W. Thompson (SI 311.155 - 3 credits)

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.

Games & UX - N. Fang (SI 311.156 - 3 credits)

Explore the industry practice of video games user research and game design. This course will put games user experience (UX) theory into practice through projects such as designing a video game. Students will come out of the course with a few portfolio pieces, including game design documentation and a pitch deck that will be pitched in-class.

AI and the Law - F. Sparr (SI 311.160 - 3 credits)

Artificial Intelligence, machine learning algorithms and other information technologies are taking on increased importance in our society. This course will examine whether the existing regulatory framework is prepared to address the moral, ethical and policy implications of these new technologies. What lessons can be drawn by recent attempts to regulate the Internet as we enter this new era of information technologies?

Graduate Courses

Visual Storytelling - J. Cruz (SI 511.073 - 3 credits)

Explore the application of visual storytelling as a means of enhancing communication, fostering collaboration, and inspiring action across teams, organizations, and broader audiences. This Master’s level course combines lectures, hands-on projects, and critical analysis of visual narratives that are relevant to design, data, and information students alike. Students will delve into storytelling & visual best practices, presentation design, data visualization, system mapping, branding, social media marketing, and more - gaining skills to craft compelling messages regardless of their roles.

Management of Analytics Teams (MAT) for High Performance - J. Thompson (SI 511.015 - 3 credits)

In this course, students will learn how to increase their skills in recruiting, evaluating, hiring, directing, and managing a high performing analytics team from the perspectives of an individual contributor, a team member, a manager, senior manager and an executive.

Generative AI + UX (SI 511.151 - 1.5 credits)

Advanced Interaction Design - J. Rampton (SI 611.151 - 3 credits)

In this course students will be asked to reinforce their understanding of interaction design methods and apply them to create realistic deliverables of advanced high fidelity designs. UI Components, Component Libraries, Style Guides, Micro Interactions, High Fidelity Prototypes will all be covered in this class. The goal is to create deliverables that would ideally be given to developers to build.

Prerequisites: SI 582 or waiver

Advanced Auto Visual Design - K. Ahn (SI 611.114 - 3 credits)

This course delves into the visual principles of automotive UX design, led by an industry expert actively working in the automotive UI field. Through practical exercises, students will gain a solid understanding of essential visual design components like typography, color, proportion, hierarchy, and layout. Students will explore the process of designing high-fidelity interfaces, progressing from initial wireframes to fully developed Graphic User Interfaces (GUI) and prototypes within the in-vehicle and mobility space. Additionally, they will learn the core concepts of UI Kits and Design Systems using Figma. By the course’s end, students will be well-versed in designing interfaces that are both functional and visually appealing.

Prerequisites: SI 520 or waiver

Behavioral & Humane Design: With Persuasion, Emotion, Trust - S. Brenton (SI 611.108 - 3 credits)

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

Prerequisites: SI 582 or waiver