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Courses

611 - Population Health Informatics

Population Health Informatics --- This course explores the foundations of population health informatics, including information architecture; data standards and confidentiality as they pertain to population health management. This course examines key concepts related to registries, electronic health records, epidemiological databases, biosurveillance, health promotion, and quality reporting in population health management.

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.

617 - Choice Architecture

Choice Architecture --- Designing a system or organization for humans requires understanding not just choice and behavior motivations (good in most cases, we hope), but also learning about the reasons we blunder and make mistakes. Thus, even when incentives are "aligned" with overall system goals, there are many instances where we make poor choices because as human beings, we are all susceptible to a wide array of routine biases that can lead to an equally wide array of unwanted and unintended outcomes and decisions. Our errors are what make us human, but up until now, they have been largely ignored by systems designers, whether these designers make complex public policy, manage a team or design an information system. But knowing how people think, we can become choice architects who design environments that both yield better decision making on the part of users, and achieve behavior that is consistent with overall system goals while gaining a competitive design-edge. The first goal of this course is to inform future information system professionals, designers and managers about human decision rules and their associated biases so that these insights can be incorporated into their design, business or management strategies. Knowledge of these issues can be a significant source of competitive advantage because they are unknown to most information systems professionals and they are not taught in most I-schools. The second goal of this course is to clarify how these results can be leveraged to create original and more effective systems and institutions that meet the designer's goals.

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.

627 - Managing and Leading the IT Org

Managing and Leading the IT Org --- Peter Drucker famously said that "Management is doing things right; leadership is doing the right things." Managing IT is about both sides of this quote, whether it is running the IT enterprise as CIO or leading an IT project. In this course, students will develop skills and techniques in the areas of strategic planning, budgeting and finance, human resources administration, vendor relationships, and leadership. Students will also explore the 4 C's of global work as applied to IT, incorporating critical thinking, communication, collaboration, and creativity. The course also explores alignment of IT initiatives with business objectives, simultaneous management of operational and development environments, and the impact of virtual organizations on IT infrastructure and services. This course is designed to be cross-disciplinary, with examples and activities drawn from information services, manufacturing, health care, public administration, higher education, non-profits, and other areas. A variety of instructional methods are used to engage students.

630 - Natural Language Processing: Algorithms and People

Natural Language Processing: Algorithms and People --- This course focuses on how to use machine learning techniques to understand, annotate, and generate the language we see in everyday situations. The techniques learned in this course can be applied to any kind of text and enable turning qualitative evaluation of text in a precise quantitative measurement. Students will learn the linguistics fundamentals of natural language processing (NLP), with specific topics of part of speech tagging, syntax and parsing, lexical semantics, topic models, and machine translation. Additional advanced topics will include sentiment analysis, crowdsourcing, and deep learning for NLP.