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Courses

602 - Mathematical Foundations for Applied Data Science

Mathematical Foundations for Applied Data Science --- This course builds and strengthens the mathematical foundations required to succeed in applied data science. The course will review fundamental concepts in statistics, probability, linear algebra, and calculus, and demonstrate how these concepts are applied to core approaches in data analysis.

605 - Interdisciplinary Problem Solving

Interdisciplinary Problem Solving --- "Interdisciplinary Problem Solving" is a course offered at the Law School through the Problem Solving Initiative (PSI). (https://problemsolving.law.umich.edu/) Through a team-based, experiential, and interdisciplinary learning model, small groups of U-M graduate and professional students work with faculty to explore and offer solutions to emerging, complex problems.

608 - Networks

Networks --- This course will cover topics in network analysis, from social networks to applications in information networks such as the internet. We will introduce basic concepts in network theory, discuss metric and models, use software analysis tools to experiment with a wide variety of real-world network data, and study applications to areas such as information retrieval. For their final project, the students will apply the concepts learned in class to networks of interest to them.

610 - Advanced Digital Studies Seminar

Advanced Digital Studies Seminar --- This graduate theory seminar provides a comprehensive and introduction to the major theories, themes and issues in Digital Studies. The course focuses on key canonical and contemporary texts in this emerging field. This course or its equivalent is required for student who wish to receive the Digital Studies Graduate Certificate.

612 - Pervasive Interaction Design

Pervasive Interaction Design --- This course is advanced interaction design course the focuses on designing interactive applications for emerging mobile and context-aware technologies. It follows a similar format to 582 (Interaction Design) in that course is studio-based, consists largely of a seminar-long group project with multiple milestones, and is supplemented by readings and discussion relevant to the topic. Class meetings consist of brief lectures to introduce and frame course concepts, design methods, and technical tools; discussion of readings; in-class design exercises; and group work/lab time. Some programming will be required in order to complete prototyping activities, though students have flexibility in choosing the platforms and languages used. Programming will not be taught in the course.

616 - Advanced Topics in Graphic Design and Communication

Advanced Topics in Graphic Design and Communication --- This multidisciplinary, hybrid course is for those students who want/need to deepen and broaden their graphic communication skills developed in SI 520: Graphic Design. This course supports students' further professional development by enhancing their conceptual problem solving skills and technical proficiency through a set of projects.

618 - Data Manipulation and Analysis

Data Manipulation and Analysis --- This course aims to help students get started with their own data harvesting, processing, aggregation, and analysis. Data analysis is crucial to evaluating and designing solutions and applications, as well as understanding user's information needs and use. In many cases the data we need to access is distributed online among many webpages, stored in a database, or available in a large text file. Often these data (e.g. web server logs) are too large to obtain and/or process manually. Instead, we need an automated way of gathering the data, parsing it, and summarizing it, before we can do more advanced analysis. Therefore, students will learn to use Python and its modules to accomplish these tasks in a 'quick and easy' yet useful and repeatable way. Next, students will learn techniques of exploratory data analysis, using scripting, text parsing, structured query language, regular expressions, graphing, and clustering methods to explore data. R modules will be used to accomplish these tasks. Students will be able to make sense of and see patterns in otherwise intractable quantities of data.

622 - Needs Assessment and Usability Evaluation

Needs Assessment and Usability Evaluation --- Covers the key concepts of evaluation and a variety of methods used to determine the goals of a system or service, performs organizational analysis, assesses task/technology or service fit, determines ease of learning of new or existing services or systems, determines ease of use, assesses aspects of performance (including information retrieval), and evaluates the success in accomplishing the user/organizational goals. Methods include observation, survey, interviews, performance analysis, evaluation in the design/iteration cycle, usability tests, and assessment of systems in use.

623 - Research Methods for Information Professionals

Research Methods for Information Professionals --- Research is key in the information professions: we assist other people conducting research, read research studies to improve practice, engage in research to evaluate tools and services, and use research in reports, funding requests, and requests for proposals. Much of our practice rests on a base of evidence and as responsible professionals it is important that we be able to weigh that evidence and apply it appropriately in our information setting. Information professionals also conduct research studies to assist in their work or for promotion within their organizations. We may also become a part or larger research teams conducting research studies. This course is designed to help you conduct and consume research studies.

624 - Healthcare Data Application, Analysis, Consulting and Communication

Healthcare Data Application, Analysis, Consulting and Communication --- Step into the role of an HI data consultant, navigate technical problems, and conduct a business analysis at the level of a research project, a Quality Improvement initiative, and a wide-spread Population-level issue. For each of the 3 real world scenarios, a stakeholder will present their business objective to the class. Students will then scope the project, explore and evaluate the data, and present deliverables.