Introduction to Accessibility --- This class is an introduction to accessibility. Students will engage in discourse on several models of disability, be exposed to different types of assistive technologies, and apply what they learn to real-world accessibility and technology challenges.

Consumer Health Informatics --- Consumer health informatics (CHI) gives health care consumers information and tools to facilitate their engagement. Students will become familiar with, and evaluate, a range of CHI applications. They will also assess the needs and technological practices of potential users, generate theory-informed design and implementation strategies, and select appropriate evaluation approaches.

Introduction to AR/VR Application Design --- This course will introduce students to Augmented Reality (AR) and Virtual Reality (VR) interfaces. This course covers basic concepts; students will create two mini-projects, one focused on AR and one on VR, using prototyping tools. The course requires neither special background nor programming experience.

Natural Language Processing --- Linguistics fundamentals of natural language processing (NLP), part of speech tagging, hidden Markov models, syntax and parsing, lexical semantics, compositional semantics, word sense disambiguation, machine translation. Additional topics such as sentiment analysis, text generation, and deep learning for NLP.

Game Theory --- Simply knowing that people behave strategically is not a recipe for success, but acquiring a framework for strategic thinking is. This course gives students the competitive edge to anticipate, formulate and analyze strategic interactions. You will learn how to acquire and process information to act effectively in strategic situations, based on analysis of the motivations of other participants. You will also learn how to incentivize the motivate users, collaborators and customers to further the objectives of an organization, community or society.

SQL and Databases --- 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 modelling, 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.

Language and Information --- This course introduces a body of quantitative techniques for modeling and analyzing natural language and for extracting useful information from texts. The theory includes Hidden Markov Models and the noisy channel model, information theory, supervised and unsupervised machine learning, and probabilistic context-free and context-sensitive grammars. Aspects of natural language analysis include phrasal lexicon induction, part of speech assignment, entity recognition, parsing, and statistical machine translation.

Introduction to Applied Data Science --- This course aims to introduce students to the basics of Data Science. Students will complete four different modules - How to be a Data Scientist, Communicating results to Stakeholders, Ethics of Data Science and Introduction to the various subspecialties of Data Science such as ML, NLP, IR, Networks, Data Mining, etc.

Creating XR Experiences --- Students gain hands-on experience with XR project management, design, development, and evaluation by working with clients from various U-M units to create XR experiences related to research and instructional programs. Weekly class lectures, readings, discussions, and assignments help to build skills and knowledge needed for creating successful XR experiences.

Intro to Cloud Computing --- In this course students will learn about cloud infrastructure, cloud networks, management, methods to compare and contrast computing services, and performance, scalability, and availability of cloud resources for data intensive tasks. Transferring of large datasets around within the cloud to create cloud based workflows will also be covered. At the end of this course, students should be able to set up cloud based workflows for doing common tasks, as well as create and explain costs and proposals. Cloud accounts will be provided to each student to meet course objectives.