Course Offerings
| Number | Title | Instructor Description | Program | Skills & Topics |
|---|---|---|---|---|
| I 301 | Introduction to Informatics | This is a survey course covering the basics of the informatics professions. We cover some history of informatics as an academic discipline and profession, review some of the significant concepts that students can expect to cover later in the Informatics major and minor, and review the different concentrations available to Informatics students. Assessment in this course is conducted through weekly quizzes and discussion questions; a short, persuasive, group presentation; and a longer-term persuasive essay project with both individual and group components. | Undergraduate |
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| I 302 | Academic Success in the Digital University | This class offers students hands-on practice with Canvas and other digital tools in order to scaffold success in the informatics program. Students will conduct an independent, iterative research project including the following steps: crafting a research question, finding and evaluating sources, and presenting information. | Undergraduate |
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| I 303 | Ethical Foundations for Informatics | Undergraduate | ||
| I 304 | Programming for Informatics | Introduction to computer programming for those without any prior knowledge or experience in computer programming. We will introduce four broad areas related to success in computer programming: language, software engineering concepts, programming environment, and practical know-how. | Undergraduate |
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| I 305 | Research Methods for Informatics | In this age of information, we repeatedly hear the phrase “Do your research!”, but what does that mean? And more importantly, why does it matter? This course is broken into two parts designed to provide a foundation to begin answering these questions: 1. The first half of the course is an introduction to research, exploring what research is, what research can look like within the field of Informatics, and how Informatics research can be leveraged for social good. 2. The second half of the course dives deeper into “research methodology,” how research is done and some of the most common tools we use to explore the field’s most burning questions. Students will learn about the functions of qualitative and quantitative methods, as well as how the pieces of the research process fit together to explore challenges and potential solutions by applying human-centered values to the intersections of information, people, and technology. This course is held in-person and rather than exams, assignments are designed to encourage students to apply course concepts to their own interests. Students will leave this course empowered as citizens to critically evaluate research in terms of process, ethics, and equity. | Undergraduate |
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| I 306 | Statistics for Informatics | We will describe data using visual and numerical descriptions (visualization and summary statistics). We will learn to make predictions and draw inferences using simple and multiple linear regression. We will learn classification using logistic regression. We will learn how to interpret diagnostic plots that accompany linear models. We will practice all these things using R and RStudio, which will be taught as part of the class. Some math and programming is not required but will be helpful in reducing the workload in the class. A statistics course is required but other statistics courses can be substituted for this one. This course counts for the Quantitative Reasoning flag, starting in Fall 2024. | Undergraduate |
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| I 310 | Topics in Introductory Informatics | Undergraduate | ||
| I 310 | Topics in Introductory Informatics: Research Methods for Informatics | Undergraduate | ||
| I 310C | Introduction to Cultural Heritage Informatics | In this class, students will first learn some fundamentals of cultural heritage informatics and be introduced to the major kinds of institutions in this space: galleries, libraries, archives, and museums. Students will also see case studies of how fundamental concepts like access or metadata get used in contemporary examples. | Undergraduate |
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| I 310D | Introduction to Human-Centered Data Science | Introduction to the theory and practice of data science through a human-centered lens, with emphasis on how design choices influence algorithmic results. Students will gain comfort and facility with fundamental principles of data science including (a) Programming for Data Science with Python (b) Data Engineering (c) Database Systems (d) Machine Learning and (e) Human centered aspects such as privacy, bias, fairness, transparency, accountability, reproducibility, interpretability, and societal implications. Each week’s class is divided into two segments: (a) Theory and Methods, a concise description of theoretical concept in data science, and (b) Tutorial, a hands-on session on applying the theory just discussed to a real-world task on publicly available data. We will use Python for programming and cover Python basics in the beginning of the course. For modules related to databases, we will use PostGre SQL. |
Undergraduate |
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| I 310J | Introduction to Social Justice Informatics | Undergraduate | ||
| I 310M | Introduction to Health Informatics | Undergraduate | ||
| I 310S | Introduction to Social Informatics | An introduction to sociotechnical perspectives on information systems, their effects, and how we intervene to make them better. | Undergraduate |
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| I 310U | Introduction to User Experience Design | This course introduces students to foundational knowledge, methods, and skills for designing human-centered user experience (UX) around interactive systems. Students will become familiar with user research, concept generation, design methods, and user evaluation. In addition, students will also learn how to collaborate in a team setting, communicate design rationales, and present compelling narratives about their work. The class will be structured with lectures, hands-on design activities such as design critiques, projects, and presentations. | Undergraduate |
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| I 320 | Topics in Informatics: Applied Cybersecurity Foundations | The Texas Cybersecurity Clinic is a two-semester sequence that first equips students with the technical and business skills of an entry-level cybersecurity analyst (semester 1) and then partners them in (supervised) teams with a small local business, municipal government, nonprofit to render pro bono cybersecurity services (semester 2). During the first semester, students will learn key cybersecurity defense concepts and skills, such as vulnerability assessment, network configuration and security, access controls, authorization techniques, responding to a cyberattack, business planning, and penetration testing. Students will also learn how to form an effective cybersecurity operations team and communicate with organization and business leaders and employees about essential cybersecurity controls and functions. By the conclusion of this course, students will be prepared to work within their assigned teams to assess, design, and render a cybersecurity improvement project plan for their client organization next semester. | Undergraduate |
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| I 320 | Topics in Informatics: Applied Cybersecurity Clinic Practicum | The Texas Cybersecurity Clinic is a two-semester sequence that first equips students with the technical and business skills of an entry-level cybersecurity analyst (semester 1) and then partners them in (supervised) teams with a Central Texas-based small business, municipal government, or nonprofit to render pro bono cybersecurity services (semester 2). During the first semester, students will learn key cybersecurity defense concepts and skills, such as vulnerability assessment, network configuration and security, access controls, authorization techniques, responding to a cyberattack, business planning, and penetration testing. Students will also learn how to form an effective cybersecurity operations team and communicate with organization leaders and employees about essential cybersecurity controls and functions. During the second semester, students work within their assigned teams to assess, design, and render a cybersecurity improvement project plan for their designated client organization, building cybersecurity capacity and bolstering the client organization’s ability to recover from a cyber incident long-term. | Undergraduate |
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| I 320 | Topics in Informatics: Blockchain, Web3, and the Internet Computer | Undergraduate | ||
| I 320 | Topics in Informatics: Designing for Healthcare | Undergraduate | ||
| I 320 | Topics in Informatics: Evaluation of Interactive Systems | Undergraduate | ||
| I 320C | Topics in Cultural Heritage Informatics: Knowledge Equity and Digital Environments | This course we will explore the concepts and values of open knowledge and knowledge equity and how they intersect with the ongoing evolution of digital environments. Open knowledge can be described as information that is freely available to the public to use and redistribute. Knowledge equity extends beyond information access and use to also include what is valued as knowledge, whom that knowledge represents, and who creates it. | Undergraduate | |
| I 320C | Topics in Cultural Heritage Informatics | Undergraduate | ||
| I 320C | Topics in Cultural Heritage Informatics: Preservation of Difficult Histories | Undergraduate | ||
| I 320C | Topics in Cultural Heritage Informatics: Archives As Data | This course introduces digital archival collections that can be accessed and used as data for research and inquiry. Topics will focus on the transformation, analysis, and interpretation of digital cultural heritage in archival contexts, including digitization, web archiving, software emulation, and data archiving. From text messages, Spotify playlists, to the President's tweets--how are digital traces collected, preserved and managed by archives? What are the ethics of managing digital archives and making them accessible to researchers, the public, and machines? | Undergraduate |
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| I 320D | Topics in Human-Centered Data Science | Undergraduate | ||
| I 320D | Topics in Human-Centered Data Science: Database Design | The class explores the principles of relational database design, and SQL as a query language in depth. | Undergraduate |
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| I 320D | Topics in Human-Centered Data Science: Data Engineering | Principles and practices in Data Engineering. Emphasis on the data engineering lifecycle and how to build data pipelines to collect, transform, analyze and visualize data from operational systems. This is a hands-on and highly interactive course. Students will learn analytical data modeling techniques for organizing and querying data. They will learn how to transform data into dimensional models, how to build data products, and how to visualize the data. We will also examine the various roles data engineers can have in an organization and career paths for data professionals | Undergraduate |
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| I 320D | Topics in Human-Centered Data Science: Applied Machine Learning with Python | This course will cover relevant fundamental concepts in machine learning (ML) and how they are used to solve real-world problems. Students will learn the theory behind a variety of machine learning tools and practice applying the tools to real-world data such as numerical data, textual data (natural language processing), and visual data (computer vision). Each class is divided into two segments: (a) Theory and Methods, a concise description of an ML concept, and (b) Lab Tutorial, a hands-on session on applying the theory just discussed to a real-world task on publicly available data. We will use Python for programming. By the end of the course, the goals for the students are to: 1. Develop a sense of where to apply machine learning and where not to, and which ML algorithm to use 2. Understand the process of garnering and preprocessing a variety of “big” real-world data, to be used to train ML systems 3. Characterize the process to train machine learning algorithms and evaluate their performance 4. Develop programming skills to code in Python and use modern ML and scientific computing libraries like SciPy and scikit-learn 5. Propose a novel product/research-focused idea (this will be an iterative process), design and execute experiments, and present the findings and demos to a suitable audience (in this case, the class). | Undergraduate |
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| I 320D | Topics in Human-Centered Data Science: Open Source Software Development | Undergraduate | ||
| I 320D | Topics in Human-Centered Data Science: Data Visualization | This course offers students in Information Science a comprehensive exploration into the theories, techniques, and tools of data visualization. It is designed to equip students with the skills to effectively communicate complex information visually, enabling data analysis and decision-making. Through a combination of lectures, hands-on projects, and case studies, students will learn how to design and implement effective and aesthetically appealing data visualizations for a variety of data types and audiences. Upon successful completion of this course, students will be able to: • Understand the principles and psychology of visual perception and how they influence data visualization. • Critically evaluate the effectiveness of different data visualization techniques for varying data types and user needs. • Master the use of leading data visualization tools and libraries such as D3.js, or Tableau. • Develop interactive dashboards and reports that effectively communicate findings to both technical and non-technical audiences. • Apply design principles to create visually appealing, accurate, and accessible data visualizations. | Undergraduate |
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| I 320D | Topics in Human-Centered Data Science: Explainable AI | Undergraduate | ||
| I 320D | Topics in Human-Centered Data Science: Text Mining and NLP Essentials | Undergraduate | ||
| I 320D | Topics in Human-Centered Data Science: Data Science for Biomedical Informatics | This course lays the foundation for data science education targeting health informatics students interested in learning more broadly about biomedical informatics. No previous coding experience is required. The students will be introduced to basic concepts and tools for data analysis. The focus is on hands-on practice and enjoyable learning. The course will use python as the programming language, and Jupyter Notebooks as the development environment (our “home base”) for the examples, tutorials, and assignments. We use Jupyterlab Notebooks because they are both the industry standard and a nice way to load, visualize, and analyze data and describe our findings in one environment. We will also learn GitHub to document changes and backup our work and, eventually, for use as a collaboration tool. Hands-on data analysis, final projects, and associated presentations will be mandatory for the completion of the course. The outcome for the class is that each student will have a GitHub repository with all of their work (Jupyter notebooks, data, etc.), including a final project that will be presented to the class. Specific topics to be covered include GitHub, Linux/Unix File system, Jupyter Notebooks, Python Programming, and Data Visualization. | Undergraduate | |
| I 320D | Topics in Human-Centered Data Science: Human-Centered Social Network Analysis | Undergraduate | ||
| I 320D | Topics in Human-Centered Data Science: Fine Tuning Open-Source Large Language Models | This course offers an introduction to Fine-Tuning Open-Source Large Language Models (LLMs) through project-based applications and real-world examples. The course will begin with a foundational understanding of Natural Language Processing (NLP), focusing on Text Preprocessing techniques such as Tokenization and Vectorization. A basic overview of Large Language Models will be provided, covering the fundamental structure and architecture of commonly used Open-Source Frameworks. The course will then focus on three key methods for fine-tuning LLMs: Self-Supervised, Supervised and Reinforcement Learning. Each method will be explored through both theoretical explanations and practical group-based projects, applying these concepts to real-world examples. Students will engage in hands-on projects to strengthen their understanding of how to customize and optimize LLMs for specific tasks or domains. | Undergraduate | |
| I 320J | Topics in Social Justice Informatics: Misinformation, Justice, and Design | In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems. | Undergraduate |
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| I 320J | Topics in Social Justice Informatics: Technologies and Information in the Global South | Undergraduate | ||
| I 320J | Topics in Social Justice Informatics: Understanding Disability and Accessibility | In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems. | Undergraduate | |
| I 320J | Topics in Social Justice Informatics | Undergraduate | ||
| I 320J | Topics in Social Justice Informatics: Design For Social Impact | This class explores how to make arguments about and through design. The first half focuses on values, criticism, ethics, and analysis of technology, the latter portion aims to help a soon-to-graduate technologist envision positive social impact in a mission-driven enterprise. Students will practice synthesizing ethical tech considerations – as they will have to do for the rest of their careers – and combining this with an organizational mindset. Through exercises, role-playing, discussions, guest lectures from activist technologists, and wide-ranging readings, students will practice connecting broader implications of their designs with technical choices. Design for Social Impact seeks to arm students with diverse ways of reflecting on their authorial relationship to technology, drawing from art and design to political science and anthropology. Course participants will be encouraged to focus on areas of personal interest, enumerating the social, political, and economic parameters of particular technical systems: parameters that are as important as power consumption, usability, or efficiency. | Undergraduate |
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| I 320J | Topics in Social Justice Informatics: Applied Social Justice Research | Undergraduate | ||
| I 320M | Topics in Health Informatics | Undergraduate | ||
| I 320M | Topics in Health Informatics: Public Health Informatics | Undergraduate | ||
| I 320M | Topics in Health Informatics: Machine Learning for Population Health Management | Undergraduate | ||
| I 320M | Topics in Health Informatics: Research Design and Analysis in Health Informatics | Undergraduate | ||
| I 320M | Topics in Health Informatics: Consumer Health Informatics | The course is designed for undergraduate students who are interested in understanding, analyzing, designing, evaluating, or developing technologies to serve the health needs of general consumers. It covers the concept of consumer health informatics, health behavior theories, health information seeking and information retrieval, various forms of consumer health systems, and the design and evaluation of such systems. | Undergraduate |
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| I 320M | Topics in Health Informatics: Data Science for Biomedical Informatics | Undergraduate | ||
| I 320S | Topics in Social Informatics: Civic Engagement and Technology | Undergraduate | ||
| I 320S | Topics in Social Informatics: Online Communities | Undergraduate | ||
| I 320S | Topics in Social Informatics: Data and Society | Explore common data collection, management, and sharing practices around information technology and emerging technologies such as AI. Students will gain hands on experiences with collecting, analyzing, and managing user data in ethical and responsible manners. Students will design data-driven systems that are centered around user consent, transparency, and social responsibilities. | Undergraduate | |
| I 320S | Topics in Social Informatics: Technologies and Information in the Global South | Undergraduate | ||
| I 320S | Topics in Social Informatics: Open Source Software Development | Undergraduate | ||
| I 320S | Topics in Social Informatics | Undergraduate | ||
| I 320S | Topics in Social Informatics: Understanding Disability and Accessibility | This course examines disability beyond digital accessibility (i.e., web accessibility, user interface design) and focuses on disability from an organizational and socio-technical point of view. Students will learn about the legislation and policies impacting accessibility, the models that shape our perceptions of disability, and review case studies of disability in several contexts. In addition to the broader types of disabilities, we will consider other forms of disabilities (permanent, situational, temporary). Students will engage in class discussions, small group activities, homework assignments, and give oral presentations. Students will be equipped with the knowledge and skills to apply methods and models of accessibility in the workplace in various fields, including software design, data science, AI, and library science. | Undergraduate |
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| I 320S | Topics in Social Informatics: Design for Social Impact | This class explores how to make arguments about and through design. The first half focuses on values, criticism, ethics, and analysis of technology, the latter portion aims to help a soon-to-graduate technologist envision positive social impact in a mission-driven enterprise. Students will practice synthesizing ethical tech considerations – as they will have to do for the rest of their careers – and combining this with an organizational mindset. Through exercises, role-playing, discussions, guest lectures from activist technologists, and wide-ranging readings, students will practice connecting broader implications of their designs with technical choices. Design for Social Impact seeks to arm students with diverse ways of reflecting on their authorial relationship to technology, drawing from art and design to political science and anthropology. Course participants will be encouraged to focus on areas of personal interest, enumerating the social, political, and economic parameters of particular technical systems: parameters that are as important as power consumption, usability, or efficiency. | Undergraduate |
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| I 320S | Topics in Social Informatics: Sociotechnical Systems Analysis | Undergraduate | ||
| I 320U | Topics in User Experience Design | Undergraduate | ||
| I 320U | Topics in User Experience Design: Misinformation, Justice, and Design | In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems. | Undergraduate |
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| I 320U | Topics in User Experience Design: Graphic Design | Undergraduate | ||
| I 320U | Topics in User Experience Design: User Research | This course addresses concepts and methods of user experience (UX) research, from identifying users’ problems and needs to evaluating concepts and designs for viability, usability, and satisfaction. It also covers aspects of managing the research process, including recruiting participants, setting up and conducting studies, analyzing qualitative and quantitative data, and disseminating insights. Students will work both individually and as part of a team to complete research exercises and projects. The course includes hands-on practice with several common UX research methods such as observation, interview, survey, focus groups, and expert review. We will also touch on applied topics such as research in enterprises, consulting, and startup organizations, lean/agile techniques, mobile research approaches, and strategies for persuasively communicating findings and product implications. | Undergraduate | |
| I 320U | Topics in User Experience Design: Information and Interaction Design | Undergraduate | ||
| I 320U | Topics in User Experience Design: Virtual Environments and Immersive Technology | Undergraduate | ||
| I 320U | Topics in User Experience Design: Digital Accessibility | Undergraduate | ||
| I 320U | Topics in User Experience Design: Understanding Human-Centered AI | This course introduces human aspects of AI systems for UX design students. It will provide an overview of AI's psychological and societal implications and the opportunities to design AI-integrated products by applying human-centered design principles. | Undergraduate |
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| I 320U | Topics in User Experience Design: 3-D Prototyping | Undergraduate | ||
| I 320U | Topics in User Experience Design: Information and Interaction Design | The first half of the course describes interaction design while the second half covers information design. Each student will keep a sketchbook and turn in sketches corresponding to exercises. No sketching experience is required. Each student will participate in a group project developing a prototype of an information artifact such as a website, app, or kiosk. The prototype is usually completed using Figma, which will be taught as part of the course. During the information design part of the course, students will be introduced to Tableau and have the opportunity to create a data visualization in Tableau. | Undergraduate |
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| I 320U | Topics in User Experience Design: Online Communities | Undergraduate | ||
| I 372 | Career Success in the Digital Organization | This course is designed to help set students majoring in Informatics up for career success post-graduation. What does career success look like? Well, philosophically many things depending on context. This course, however, focuses on the transition between the last year of college and the first year of a career. The semester is broken into three units as a foundation to begin answering these questions: 1. The Landscape: What opportunities exist for graduates with my skillsets and interests? What do different job titles actually mean? How do I know which path is right for me? How do I find jobs and opportunities I’m interested in and qualified for? 2. The Application & Interview Process: After Unit 1, I know the kinds of positions and career paths I’m interested in post-graduation, but how I do actually get the job/position or accepted to my program of interest? In a sea of hundreds (sometimes thousands) of applicants, how do I show I’m a good fit in an application and an interview? Once I have options, how do I choose what’s right for me? 3. The First Year: How do I make sure my first year is successful? How do I navigate a new professional space? How do I set myself up to build relationships and perform well? How do I apply what I’ve learned in the Informatics Major and at UT to grow as an ethical, equitable leader and information professional? This course is held in-person and rather than exams, assignments are built as concrete materials students can use in their career searches and professional endeavors. Students will leave this course empowered to successfully navigate the Informatics-related job market and professional opportunities | Undergraduate |
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| I 178I | Independent Study | Undergraduate | ||
| I 278I | Independent Study | Undergraduate | ||
| I 378I | Independent Study | Undergraduate | ||
| I 178R | Research Experience | Undergraduate | ||
| I 278R | Research Experience | Undergraduate | ||
| I 378R | Research Experience | Undergraduate | ||
| I 178T | Internship | Undergraduate | ||
| I 278T | Internship | Undergraduate | ||
| I 378T | Internship | Undergraduate | ||
| I 379C | Capstone | As the culminating experience of the undergraduate Informatics Program, I 379C allows every student to apply their unique skillsets and learnings to a "degree-capping" project that is focused on a real-world problem or initiative. Informatics Capstone projects can take many forms, but typically involve aligning on a specific project and plan with an industry or faculty project sponsor, and then completing the project over the course of the semester. This course is designed to support your capstone journey throughout the semester as you work on your project with your Field Supervisor. Progress in the course is measured through weekly updates and documents submitted directly to Canvas. During the semester, the course meets once per week, and during these sessions we'll focus on items and issues relevant to your capstone experience. You'll have an opportunity to present your work also, through class presentations and the final poster session where your sponsors, faculty, and other students can meet you and discuss your project. Summary of Course Goals 1. Deliver a professional-level project/solution to showcase your knowledge, skills, and abilities. 2. Take direction and feedback from a supervisor working in your applied field of study. 3. Strengthen communication and presentation skills. 4. Manage expectations around project goals, schedule, and deliverables. | Undergraduate |
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| I 679HA | Honors Thesis | Undergraduate | ||
| I 679HB | Honors Thesis | Undergraduate | ||
| ISP 380 | Introduction to Information Security and Privacy | ISP | ||
| INF 380E | Perspectives on Information | In this class we'll use history and readings to not only understand the current state of the information field, but how we got here. Seeing that, students will understand that they have the power to shape and improve the information field. Students will also work in in-class teams to cement ideas and connect to other students in the class. We work to answer the question of why UX designers, archivists, AI ethicists, and librarians are all in the same graduate program. Ultimately the goal is to connect, understand, and inspire. | MSIS/PhD |
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| INF 380P | Introduction to Programming | The class focuses on developing problem solving skills using Python as a programming language. Starting from procedural function development, we also explore object-oriented techniques, and discuss simple data structures that are often used in software development. The students usually do a few programming assignments, take a midterm, and submit a final project. | MSIS/PhD |
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| INF 181 | Individual Studies (1 credit hour) | MSIS/PhD | ||
| INF 281 | Individual Studies (2 credit hours) | MSIS/PhD | ||
| ISP 381 | Information and Privacy in Society | ISP | ||
| INF 381 | Individual Studies (3 credit hours) | MSIS/PhD | ||
| ISP 382 | Public Policy, Information Security, and Privacy | ISP | ||
| INF 382C | Understanding and Serving Users | What does it really mean to be user-centered? How do we practice user-centered design in a professional and methodical manner? What research findings can we rely on to help us improve user experiences? This is a readings/discussion course that examines in depth what we know about people (that is, what does scientific research actually tell us) and how can we apply this knowledge in the real-world of experience design. We examine human psychology, from physical ergonomics to cultural dispositions, stopping off on cognition and social analyses en route, so as to have a holistic, robust perspective on what it means to understand users. The readings are complemented with an examination of methods e.g., what is a cognitive walkthrough and how do you do it reliably? what are the limitations of heuristic evaluations? The goal is to give you a solid grounding in the practices of user-centered thinking, regardless of your area of application, and prepare you for professional level contributions in the user-experience world. There is no teamwork, all students deliver individual term papers and design critique diaries. There are also no pre-requisites -- technical or theoretical, the class is open to all. | MSIS/PhD |
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| INF 382D | Introduction to Information Resources and Services | MSIS/PhD | ||
| INF 382G | Information Resources and Services for Children and Young Adults | MSIS/PhD | ||
| INF 382G.03 | Materials for Children and Young Adults | MSIS/PhD | ||
| INF 382H | Legal Information Resources | In this course, you will gain exposure to legal reference questions and the reference interview, investigate legal research sources, and beome familiar with the methods and strategies for conducting legal reference and basic legal research. | MSIS/PhD |
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| INF 382L | Information Resources and Services | MSIS/PhD | ||
| INF 382L | Information Resources and Services: Scholarly Communication | With the ongoing evolution of digital technologies, the creation and sharing of scholarly knowledge continues to change rapidly. In this course, we will explore historical developments, current issues, and ongoing debates in scholarly communication. We will also examine the critical roles of academic libraries and library professionals in the complex scholarly communication landscape. As we learn about topics such as academic publishing, open access and open scholarship, peer review, metrics and impact, copyright and fair use, open education, library values, and social justice, we will consider challenges and opportunities for librarians engaged in scholarly communication. In addition to building a broad understanding of key issues and areas of scholarly communication, students will develop more in-depth knowledge of a scholarly communication issue. | MSIS/PhD | |
| INF 382L.03 | Inquiry and Information Seeking in K-12 | Examine inquiry models and information-seeking theories relevant to K-12 teaching and learning. Explore tools and resources for student learning and strategies for teaching specific information literacy skills within the context of a research-based inquiry. | MSIS/PhD |
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| INF 382S | Library Instruction and Information Literacy | History and ongoing evolution of instruction in library and information service settings; conceptions of information literacy; learning theories and pedagogical approaches; instructional design principles, including backward design; and reflective teaching practice. | MSIS/PhD |
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| ISP 383 | Business Governance and Controls for Information Security and Privacy | ISP | ||
| INF 383H | Introduction to Digital Humanities | This course is a hands-on introduction to Digital Humanities, which may be defined as using digital technologies to investigate questions traditional to the humanities or to ask humanities-oriented questions about the digital. What are these questions? As usual, it depends, depends on the scholar’s theoretical orientation, methods, and resources at hand (including not only primary source materials, but time, skill, and support). This course is relevant to literary scholars, historians, media scholars, information scholars, and all those who are interested in how humanists engage in cultural studies. It will include learning to evaluate DH questions and DH projects through project-based exercises in creating and interpreting digital humanities resources and tools and a close (and critical) look at the infrastructural, institutional, and political issues involved in interrogating “the digital” in the humanities. As we look at the concepts, methods, theories, and resources of DH through the perspective of practice, we will consider how computational methods are being used to further humanities research but also, more importantly, how our understanding of computing technologies is deepened by humanities research. No prerequisites are required for this course. | MSIS/PhD |
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| ISP 384 | Strategic Communication for Information Security and Privacy | ISP | ||
| INF 384C | Organizing Information | MSIS/PhD | ||
| INF 384D | Collection Management | MSIS/PhD | ||
| INF 384H | Concepts of Information Retrieval | MSIS/PhD | ||
| INF 384M | Topics In Description and Metadata | MSIS/PhD | ||
| INF 384M | Topics In Description and Metadata: Theories and Applications of Metadata | MSIS/PhD | ||
| ISP 385 | Information Risk and Benefit Analysis | ISP | ||
| INF 385C | Human-Computer Interaction | This course introduces students to human-computer interaction theories and design processes. The emphasis is on applied user experience (UX) design. However, the course starts by discussing fundamental aspects of human perception and cognition and linking them with design principles. The course presents an iterative evaluation-centered UX lifecycle and introduces students to a broader notion of user experience, including usability, usefulness, and emotional impact. The UX lifecycle should be viewed as template intended to be instantiated in many different ways to match the constraints of a particular development project. The UX lifecycle activities we cover include contextual inquiry and analysis, requirements extraction, design-informing models, design thinking, ideation, sketching, conceptual design, and formative evaluation. | MSIS/PhD |
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| INF 385E | Information Architecture and Design | This course explores the fundamental principles and practical applications of Information Architecture (IA). Drawing from the seminal work "Information Architecture: For the Web and Beyond" by Louis Rosenfeld, Peter Morville, and Jorge Arango, students will delve into the essential concepts, methodologies, and best practices shaping the organization and presentation of information in digital environments. Simply, this course addresses how to make content organized and findable based on human understanding. Throughout the course, students will examine the critical role of IA in enhancing user experience, facilitating navigation, and optimizing content discoverability. Topics covered include information organization, navigation design, metadata implementation, taxonomy development, and user-centered design principles. Through a combination of theoretical discussions, case studies, hands-on exercises, and a real project with a real client and real world constraints, students will gain proficiency in designing effective IA solutions tailored to diverse user needs and contexts. Emphasis will be placed on understanding user behavior, conducting user research, and iteratively refining IA structures to align with evolving user requirements and organizational goals. Course Objectives: Gain a comprehensive understanding of Information Architecture principles and methodologies. Learn how to analyze and evaluate existing IA structures in digital environments. Develop proficiency in designing and implementing effective IA solutions for websites and digital products. Explore techniques for conducting user research and applying user-centered design principles to IA. Understand the role of IA in enhancing usability, findability, and overall user experience. Acquire practical skills in wireframing, prototyping, and usability testing within an IA context. Explore emerging trends and technologies shaping the field of Information Architecture. | MSIS/PhD |
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| INF 385M | Database Management | Database is the foundation of Data Science. It provides the unique design to store, retrieve, and manage data. Data become the essential gas to power the generative AI. How to model data, encode context, enforce business rules, and achieve efficiency are critical for database design. This course provides the introductory understanding of relational database design with the focus on three parts. The first part is centered around the database design lifecycle by introducing business rules, ER diagram, normalization, and UML chart. The second part talks about database query language SQL by explaining concepts and providing examples. The third part gives you the forward introduction of XML database which is the commonly used NoSQL database. The learning content will be delivered in the variety of exercises including lectures, tutorials, class activities, individual assignments, group assignments, and group projects. This course empathizes peer learning, hands-on practices, forward exploring, and risk taking. | MSIS/PhD |
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| INF 385N | Informatics: Consumer Health Informatics | MSIS/PhD | ||
| INF 385P | Usability | This course will give students a foundational introduction to user experience (also known as UX, CX, HCI) and introduce some of the core UX research methods in use today, as well as applying these methods to a product to create a final presentation that can hopefully be used in their portfolio/job seeking adventures. Accordingly, the class will cover 5 major areas: 1. Have an in-depth understanding of some primary UX methods relevant to product development (e.g. Heuristic evaluation, Moderated User testing, UX Benchmarking). 2. Understand the principles of other important UX tools/methods (e.g. Information architecture tests (card-sorts), RITE testing, Competitive Analysis, Thematic coding of qualitative data, etc.). 3. Have a working understanding of the most frequently used UX methods at each point of the development lifecycle, with a specific focus on which methods are best suited to evaluative research. 4. Learn the scientific underpinnings of the various methodologies, including the specific advantages and disadvantages of each. 5. The “real world” application of these skills to industry-paced projects | MSIS/PhD |
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| INF 385R | Survey of Digitization | MSIS/PhD | ||
| INF 385S | Digital Libraries | This course explores the life cycle of a digital library/collection through various critical lenses and hands-on experiences. The objective of the course is for students to obtain a solid understanding of the theoretical frameworks, technical processes, and technologies needed to build meaningful, ethical, and reusable digital libraries. | MSIS/PhD |
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| ISP 385T | Topics in Information Security and Privacy | ISP | ||
| INF 385T | Special Topics in Information Science | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: AI in Health | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Designing User Interfaces for Children | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Responsible Data Management | Explore common data collection, management, and sharing practices in information technology and emerging technologies, such as search engines and AI systems. Students will read papers and engage in discussions about the pros and cons of established data practices and learn about the three main components of responsible data management: 1) consent and ownership, 2) privacy and anonymity, and 3) broader impact. Students will also practice how to collect data, make data-driven decisions, and design data-driven products through group projects as UX designers, researchers, and data scientists. The course will bring in interdisciplinary perspectives with guest speakers from archive science, engineering, and respponsible AI, to provide a holistic view of broader data ecosystems and infrastructures. | MSIS/PhD | |
| INF 385T | Special Topics in Information Science: Quantifying UX | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: UX and Product Management | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Javascript Programming | This course is tailored for graduate students in Information Science who wish to deepen their understanding and skills in JavaScript, a cornerstone technology of the web. The course bridges theoretical concepts with practical application, preparing students to tackle complex problems in data processing, visualization, and web development within the realm of Information Science. The course incorporates multiple ways of learning including: readings, lectures, class discussion, in-class pair programming exercises, and project-base learning. Upon completion of this course, students will: • Gain an in-depth understanding of JavaScript's core concepts, including ES6+ features, asynchronous programming, and the event loop. • Learn to efficiently manipulate and process data using JavaScript, leveraging its interaction with APIs, and other web technologies. • Develop skills in creating interactive and dynamic data visualizations using packages such as D3.js or and other JavaScript-based visualization tools. • Understand the principles of web security, performance optimization, and best practices in JavaScript coding standards. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Applied Experiments and Measurement | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Library Foundations | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Electronic Discovery and Digital Evidence | Cross-listing of LAW 386N hosted by the School of Law. Explore the hottest topics in litigation today: electronic evidence and digital discovery (including emerging roles for AI). Evidence is information, and nearly all information is created, collected, communicated and stored electronically. Thus, the ability to identify, preserve, interpret, authenticate and challenge electronically stored information is a crucial litigation skill. This course seeks to reconcile the federal rules and e-discovery case law with the sources, forms and methods of information technology and computer forensics. Students will explore the roots of information technology, learn to "speak geek" see information with "new eyes" and acquire hands-on, practical training in finding electronic evidence, meeting preservation duties, guarding against spoliation, selecting forms of production, communicating and cooperating with opposing counsel and managing the volume and variety of digital evidence and metadata. You will use real world software tools and emerge with an understanding of the nuts and bolts of information technology and discovery, No prior background in law, computing or technology is required to succeed. | MSIS/PhD | |
| INF 385T | Special Topics in Information Science: Nonprofit Management and Strategy | This course examines key issues, challenges, and opportunities in the creation, management, and leadership of nonprofit organizations. Attention is given both to internal organizational issues and to nonprofits’ relationships with key external constituencies. Among the topics to be considered are nonprofit creation, mission management, organizational leadership, funding strategies, partnerships, and the impact of the public policy environment. Readings and discussion will examine nonprofits in varied fields of activity (such as human services and culture). Assignments and exercises will be employed to help develop presentation and grant writing skills. The course is organized in a seminar format and will employ exercises and cases to translate broad themes to practical issues related to nonprofit strategy and management. Guest speakers will periodically join us to share their own experiences building and running nonprofits (additional speakers may be added). | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: UX Hardware Design in the Corporate World | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Foundations of Data Science | This class explores various data science models, both traditional and the state of the art techniques. The course is designed to provide mathematical and computational basis such as Linear Algebra, Optimization techniques, and probabilistic modeling for different types of machine learning models. The goal of the class is provide a foundational basis for data science techniques. The class focuses on PSETs and a final data science project. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Knowledge Infrastructures and Management | Infrastructure is all around us, even (or perhaps especially) where we do not actively consider or account for it. In this course, students will learn how knowledge infrastructures such as repositories, classification systems, databases, networks, standards, and/or metadata both shape and are shaped by governmental policy, institutional decision making, technical advances, and professional and personal value systems. We consider how infrastructure matters in professional, personal, and political life, and employ infrastructure as a lens to evaluate and understand the legal, ethical, and policy consequences of knowledge work, data science, and information management. In this course, students will employ an infrastructural perspective to evaluate programs, systems, policies, and/or organizations. We will explore the consequences and societal impact of knowledge work at both global and local scales, and consider how infrastructure might be built or refined to support societal or organizational goals such as social justice, privacy, innovation, health, or security. This is primarily a discussion-oriented course, with assessment primarily coming through a multi-stage, semester-long, project oriented around a program evaluation. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Prompt Engineering | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Critical Data Studies | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Product Management | As an industry practitioner with over a dozen years of product management experience and a dozen years of experience as a UX professional, I'm really looking forward to teaching a course that melds these best of both worlds. This course will focus on the fundamentals of product management and the tools and techniques employed by product managers. Students will learn about the corporate product phase gates and all the cross-functional teams with whom product managers engage. The product journey will be examined exploring: 1) how successful products are conceived; 2) how they intercept and are matched with appropriate technologies at the right time; 3) how their markets are analyzed; 4) how their volumes, revenues and profits are forecast yielding their business cases; and 5) how their value propositions are communicated to corporate executives to be formally approved and added to a company’s product roadmap. Furthermore, software and hardware product development processes will be investigated with an emphasis on how UX professionals can help streamline these processes and deliver user experiences that delight customers. This will have the effect of strengthening the product’s business case and ultimately the product’s return on investment (ROI), providing an evangelization opportunity for the product, the company, the product manager, and the UX professional. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Civic Engagement and Technology | Civic engagement involves joining with others to identify and address issues facing a community. Examples include volunteering to clean up a park, participating in a town hall meeting, and voting. Conversations about civic issues emerge in many public and private spaces, including public libraries, coffeeshops, and through group messaging platforms, like WhatsApp. This course will investigate how computing systems have been used to help people surface issues in various ways---from community sensing systems to crowdsourcing budget issues---as well as address issues through online discussion, mutual-aid, and coordinating volunteer networks. Technology can serve as a force multiplier for civic engagement; however, there are important considerations related to their design, deployment, and sustaining them over time. Civic technology is embedded within a policy, political, and technical environment that can be tricky to navigate. Many people also lack access to the time and training to fully engage with a technology; failure to recognize these barriers related to the “digital divide” can result in systematically preventing some groups of people from participating in civic activities. Additionally, there may be unanticipated risks associated with the way that a civic technology collects, manages, and shares personal as well as group level information. These ethical issues deserve special consideration in a civic engagement and socio-technical context. | MSIS/PhD | |
| INF 385T | Special Topics in Information Science: Explainable Artificial Intelligence | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Rapid Prototyping and Lean UX Methodology | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Intersections of Surveillance and Society | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Inclusive Design for Accessible Technology | This course introduces the theory and practice of inclusive design principles for developing accessible technology. Inclusive design focuses on understanding the diversity of human characteristics (e.g., age, gender, race/ethnicity, disability, etc.) and applying a human-centered approach in designing technology to satisfy user requirements. Students will learn to use inclusive design processes to recognize user characteristics, discover user needs, produce design solutions, and develop prototypes during this course. Topics include, but are not limited to, inclusive design, ability-based design, disability-related terminology, and assistive technologies. Students will be required to engage in class discussions, complete in-class and homework assignments, give oral presentations, work in small groups, and complete a semester project. This course assumes students will have prior knowledge or experience in user experience (UX) design and/or human-computer interaction. No prior programming experience is required. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Ethnography and Socio-Technical Futures | Ethnographic research has found application and acceptance across various academic disciplines as well as industries. This course aims to introduce fundamental tenets of ethnographic methodology for investigating sociotechnical systems. Its foundation rests on interdisciplinary perspectives and anthropological insights, while simultaneously aligning with contemporary advancements such as design and speculative ethnography. The role of the future has perpetually held a central position in the utilization and shaping of technologies and information systems. A recurring narrative involves positioning a specific technology or system as "revolutionary" or "the future of" a certain domain. Adopting an ethnographic approach, this course seeks to critically examine sociotechnical imaginaries. Its objective is to glean insights from diverse communities, offering guidance in the construction of futures that are more inclusive, equitable, and diverse. | MSIS/PhD | |
| INF 385T | Special Topics in Information Science: Visual Design | In this course, students will learn about the graphic designs role in UX design roles using industry-standard tools, Figma and Adobe Illustrator. This course is meant to engage and push students to think creatively to design and create portfolio-worthy polished designs. Students will learn to craft visually engaging and user-friendly digital experiences. By learning and understanding graphic design principles, including typography, color theory, and layout design, students will develop proficiency in designing and prototyping for a variety of experiences. These skills will be displayed through design exercises and projects. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Ethics of AI: Theorizing Good Systems | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Virtual Environments | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Disaster Planning and Response | Disaster events, like floods and fires, can cause severe damage and loss in cultural heritage collections. How will you respond when disaster strikes? This course introduces students to the fundamental preservation concepts, planning strategies, and applied response techniques that make a difference. The class will evaluate the physical impact of fire, water, soot, mold, and insects on varied media, including books, flat paper, audiovisual materials, and other items. Disaster planning exercises model proactive methods to minimize damage. Hands-on response drills enable students to practice salvage techniques, and to triage and prioritize impacted materials. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Data Semantics | The current Web has experienced tremendous changes to connect data, people, and knowledge. There are a couple of exciting efforts trying to bring the Web to its full potential. The Semantic Web is one of them which is heavily embedded in the Artificial Intelligence area with the long-term goal to enhance the human and machine interaction by representing data semantics, integrating data silos, and enabling intelligent search and discovery. This course aims to provide the basic overview of the Semantic Web in general, and data semantics in particular, and how they can be applied to enhance data integration and knowledge inference. Ontology is the backbone of the Semantic Web. It models the semantics of data and represents them in markup languages proposed by the World Wide Web Consortium (W3C). W3C plays a significant role in directing major efforts at specifying, developing, and deploying standards for sharing information. Semantically enriched data paves the crucial way to facilitate the Web functionality and interoperability. This course contains three parts: Semantic Web language, RDF graph database (i.e., RDF triple store), and its applications. The fundamental part of the course is the Semantic Web languages. It starts from XML and goes further to RDF and OWL. The RDF graph database part introduces different APIs of Jena and its reasoners. The application part showcases current trends on semantic applications. Prerequisites Basic knowledge of HTML and XML is desired. Course Objectives This course aims to develop a critical appreciation of semantic technologies as they are currently being developed. At the end of this course, students should be able to: • sketch the overall architecture of the Semantic Web. • identify the major technologies of the Semantic Web and explain their roles. • illustrate the design principles of the Semantic Web by applying the technologies. • understand certain limitations of the Semantic Web technologies, and be aware of the kinds of services it can and cannot deliver. Course aims are achieved through: • Lectures covers basic knowledge of the Semantic Web • Projects applying semantic technologies to concrete problems of information delivery and use • Assignments of practicing and utilizing key semantic technologies | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Misinformation and Disinformation | In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Data Storytelling | Data storytelling is more than sharing data—at its most simple, it’s about designing charts and tables that make sense to the people who will be using them and help those people make better, faster decisions. While making a chart is as easy as a few clicks, doing it well requires much more. There is a science to how our eyes and minds process information as well as an art to making good graphic design choices. This comes together in an effective data presentation when the work is readable, usable, and above all actionable—not just aesthetically pleasing (though we’ll certainly address that too). As information professionals, we are well-positioned to understand and design for the needs of our users, to interrogate our data sources thoughtfully, and to ask future-thinking questions. This course will also draw on elements from cognitive psychology, user experience, data journalism, graphic design, business, and more. This multidisciplinary approach will take us on a grand tour that will touch on many aspects of data analysis and will serve as an excellent introduction to other data-oriented courses in the iSchool master’s program. | MSIS/PhD | |
| INF 385T | Special Topics in Information Science: Mapping For The Common Good | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Digital Forensics and Incident Response | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Digital Equity, Justice, Opportunity, and Inclusion | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Accessible UX | Accessible UX provides students working (or planning to work) in any area of UX, Digital Product Management, or Development with key skills and insights into the current accessibility landscape, in addition to specific guidelines and WCAG conformance specifications. The course is divided into foundational and tactical modules. The first half of the course provides a comprehensive overview of Accessibility and its importance. The second half of the course involves evaluating real-world applications and websites per the WCAG guidelines, producing Accessibility reports, planning studies (with persons with disabilities), and designing for accessibility. Course Goals 1. Become proficient in recognizing accessibility issues in key domains 2. Understand successful team and organizational behaviors in Accessibility 3. Learn how Accessible UX and Development is accomplished 4. Evaluate Web and App experiences using the WCAG framework from W3.org/WAI | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Digital Text Analysis | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Community Engagement and Services | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: User Behavior and Search Experience | The purpose of this course is to provide theoretical and practical foundations for information professionals who wish to design and evaluate search systems and services, taking user-centered approaches. This course explores search user interfaces, search behavior, search interaction, search user experience, search as learning, search for creativity, and research methods for understanding information behavior and evaluating search systems. Students will learn search behavior across various contexts, including academic and professional settings, everyday life, and digital learning environments. Students will gain insights into how people interact with, use, and evaluate information in a variety of application areas, such as web search engines, domain-specific search systems, digital libraries, social search platforms, and generative AI-based systems. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Seminar in Propaganda, Deception and Manipulation in the Technology Era | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Product and Project Management | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Concepts and Practices in Information Security | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Introduction to Machine Learning | This course will cover fundamental concepts in Machine Learning (ML). The course will provide conceptual and practical knowledge on a wide range of modern machine learning algorithms; including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), reinforcement learning & deep learning models (CNN, RNN, Autoencoders & Transformers) and also introduce the importance of Prompt Engineering and Retrieval Augmented Generation. The goal is for students to be comfortable and confident in machine learning concepts and have the ablity to build machine learning model solution to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, this is a great place to start. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Blockchain, Web3, and the Internet Computer | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Natural Language Processing and Applications | Natural Language Processing (NLP) is concerned with interactions between computers and humans through the medium of human languages. It involves analyzing, understanding, and generating human language, making it possible for machines to interpret and respond to human speech and text. NLP is currently making significant contributions to modern technological advancements and serves as the backbone of crucial applications such as Gen AI, Conversational AI, Question Answering, Human Language Translation, Summarization, Sentiment and Emotion Analysis, Search and Recommendation, and Information Extraction in various domains such as healthcare, finance, legal, libraries and education and beyond. The proposed graduate-level course aims to cover fundamental concepts in Natural Language Processing / Computational Linguistics and how they are used to solve real-world problems. Classes in each week will be divided into two segments: (a) Theory and Methods, a concise description of an NLP concept, and (b) Practicum, a hands-on session on applying the theory to a real-world task on publicly available multilingual text datasets. We will use Python for programming along with popular libraries for text processing such as NLTK, SpaCy and HuggingFace's transformers. By the end of the course, the goals for the students are to: 1. Understand the process of garnering and pre-processing a large amount of multilingual textual data from various domains and sources. Characterize the processes to store, load, pre-process multilingual data and apply language processing operations such as normalization, tokenization, lemmatization, chunking and machine readable representation (vector) extraction. 2. Train machine learning algorithms for natural language understanding and generation and evaluate their performance. 3. Learn to extract information from unstructured text and represent them in the form of knowledge graphs 4. Learn to use existing knowledge graphs, ontologies and lexical knowledge networks for predictive analysis on text 5. Learn about popular NLP applications and tasks and the process of building such applications 6. Propose a novel product/research-focused idea (this will be an iterative process), design and execute experiments, and present the findings and demos to a suitable audience (in this case, the class). | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Deep Learning and Multimodal Systems | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Datafication and Its Consequences | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Web Application Development | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Computer Vision | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: UX Prototyping | Students will learn to produce prototypes of information artifacts such as websites or apps, usually using Figma. The prototypes will be completed in groups. Students will also keep a sketchbook throughout the semester and will complete sketching exercises. No previous sketching experience is required. Students will learn the difference between lofi and hifi prototypes and complete examples of both. Lectures will describe prototyping in different forms and will also describe activities that support prototyping. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Program Evaluation in Libraries | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Computational Social Science Methods | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Community Engagement in Libraries | MSIS/PhD | ||
| INF 385T | Special Topics in Information Science: Games in Libraries, Archives, and Museums | In this class, we will explore different strategies for including games in collections across libraries, archives, and museums using case studies of specific institutions. We will also address unique qualities of digital and board games that make them challenging to existing practice in the field. Students will have hands-on experience with games through the semester. | MSIS/PhD |
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| INF 385T | Special Topics in Information Science: Designing Physical Information Systems | MSIS/PhD | ||
| INF 385T.01 | Special Topics in Information Science: Presenting Information | MSIS/PhD | ||
| INF 385T.02 | Special Topics in Information Science: Visualization | MSIS/PhD | ||
| INF 385T.03 | Special Topics in Information Science: Human Computation and Crowdsourcing | MSIS/PhD | ||
| INF 385T.09 | Special Topics in Information Science: Data Wrangling | Learning key data wrangling maneuvers in abstract and implementations in SQL, Excel, R Tidyverse, and Python Pandas. Maneuvers in data transformations include Nest, Pivot, Mutate (inc. separate/unite), Group/Summarize and Rectangling. Projects include working with "wild caught" data datasets (usually CSV or JSON) and computational notebook environments (e.g., iPython, Jupyter, Rmarkdown, Quarto). Fall 2024 has changes from previous syllabus now that we have Database Design and Introduction to Programming. Nonetheless, the previous syllabus is still useful as it links to course materials that show the teaching approach and type of assignments. http://howisonlab.github.io/datawrangling/#Schedule_of_classes | MSIS/PhD |
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| INF 385T.10 | Special Topics in Information Science: Interaction Design | This team-oriented project course will explore several issues surrounding the design and production of usable and elegant interactive experiences. Students will be introduced to topics including the iterative design process, physical and digital prototyping, and user testing. Project work will allow students to demonstrate mastery of the methods discussed in class through the creation and evaluation of screen-based and physical interfaces. Nor formal programming experience is necessary or expected as students are encouraged to leverage existing skills to develop visualizations and prototypes. For projects in the digital domain, experience with Figma, HTML5, Axure, Invision or the like is helpful, but not required. | MSIS/PhD |
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| INF 385T.12 | Special Topics in Information Science: Ethics of AI | Artificial intelligence (AI) is both a product of and a major influence on society. As AI plays an increasingly important role in society, it is critical to understand both the ethical factors that influence the design of AI and the ethical dimensions of the impacts of AI in society. The goal of this course is to prepare students for the important ethical responsibilities that come with developing systems that may have consequential, even life-and-death, consequences. Students first learn about both the history of ethics and the history of AI, to understand the basis for contemporary, global ethical perspectives (including non-Western and feminist perspectives) and the factors that have influenced the design, development, and deployment of AI-based systems. Students then explore the societal dimensions of the ethics and values of AI. Finally, students explore the technical dimensions of the ethics and values of AI, including design considerations such as fairness, accountability, transparency, power, and agency. Students who perform well in this class will be positioned to take on a leadership role within their organizations and will be able to help guide and steer the design, development, and deployment of AI-based systems in ways that benefit users, other stakeholders, their organizations, and society. The knowledge and skill gained through this course will benefit students throughout their careers, and society as a whole will benefit from ensuring that studenrs are prepared to consider the important ethical dimensions of their work. | MSIS/PhD |
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| INF 385T.13 | Special Topics in Information Science: Human-AI Interaction | MSIS/PhD | ||
| INF 385V | Health Informatics | MSIS/PhD | ||
| ISP 386 | Information Security | ISP | ||
| INF 386 | History of Information and Society: History of Information in the United States | MSIS/PhD | ||
| INF 386E | Information and Culture: Planning and Understanding Exhibits | Exhibits are a powerful way for libraries, archives, museums, and cultural institutions to engage the public with their collections. This course offers students the opportunity to plan and install an exhibit, focusing on objectives such as: crafting a narrative around physical objects; drafting exhibit text; accommodating media preservation issues; building basic display supports; and publicizing the exhibit. Students will learn about the historical origins of modern-day exhibit practices and will visit and evaluate current exhibits on campus and in the Austin area. | MSIS/PhD |
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| INF 386E | Information and Culture: Arts Organizations, Community Engagement, and Policy | Cross-listing of P A 385D, hosted by the LBJ School of Public Affairs. Examine key topics in the management and leadership of arts and cultural organizations, with particular attention to how arts organizations engage (or fail to engage) external constituencies, and the significance of private and public policies. While commercial forms will be considered for purposes of comparison, our primary focus will be on nonprofit organizations. Examples of topics include mission management, organizational leadership, the role of boards of directors, funding strategies, audience engagement, community engagement and relationships, arts advocacy, and policies that create challenges and opportunities for arts organizations and participation. The class will employ exercises and cases to translate broad themes to practical issues in arts management and community engagement. Guest speakers will periodically join us to share their experiences. Relevant to students planning to work in, with, or through nonprofit arts and cultural organizations. | MSIS/PhD | |
| INF 386E | Information and Culture | MSIS/PhD | ||
| ISP 387 | Information Management and Repositories | ISP | ||
| INF 387 | Administration | MSIS/PhD | ||
| INF 387.05 | School Library Management I | Designed for students pursuing Texas Education Agency (TEA) certification in school librarianship. Examine the philosophy, objectives, and management of the school library with an emphasis on standards and competencies, and the roles of the school librari | MSIS/PhD |
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| INF 387.06 | School Library Management II | Designed for students pursuing Texas Education Agency (TEA) certification in school librarianship. Examine the philosophy, objectives, standards, and management of the school library with an emphasis on the roles of the school librarian as an instructiona | MSIS/PhD |
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| INF 387C | Managing Information Organizations | This course will develop your skills to effectively manage a library, or information organization. We’ll be looking at problems faced by many types of libraries: public, academic, school, special. We’ll examine staffing, budget, collection development, patron behavior, and managing the expectations of users. | MSIS/PhD |
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| ISP 388 | Law Governing Information Security and Privacy | ISP | ||
| INF 388E | Historical Museums: Context and Practice | MSIS/PhD | ||
| ISP 388L | Professional Experience and Project | ISP | ||
| INF 388L | Professional Experience and Project | As the culminating experience of the MSIS program, INF 388L allows every student to apply their unique skillsets and learnings to a professional project that is focused on a real-world problem or initiative. The course is designed to support your capstone journey throughout the semester as you work on your project with your project Field Supervisor. As an asynchronous course, students and instructors communicate via Canvas and various discussion prompts. Progress in the course is measured through updates and documents submitted directly to Canvas. During the semester, time is allotted for 1-on-1 meetings between student and instructor, and for small group meetings, as needed. Summary of Course Goals 1. Deliver a professional-level project/solution to showcase your knowledge, skills, and abilities. 2. Take direction and feedback from a supervisor working in your applied field of study. 3. Strengthen communication and presentation skills. 4. Manage expectations around project goals, schedule, and deliverables. | MSIS/PhD |
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| INF 388R | Practicum in School Libraries | Designed for students pursuing Texas Education Agency (TEA) certification in school librarianship. 160 hours of field work in varied school library settings under the supervision of a qualified field supervisor and site supervisor. | MSIS/PhD |
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| INF 188T | Internship in Libraries and Other Information Agencies | MSIS/PhD | ||
| INF 288T | Internship in Libraries and Other Information Agencies | MSIS/PhD | ||
| INF 388T | Internship in Libraries and Other Information Agencies | MSIS/PhD | ||
| ISP 189 | Individual Studies | ISP | ||
| ISP 289 | Individual Studies | ISP | ||
| ISP 389 | Individual Studies | ISP | ||
| INF 389E | Introduction to Records Management | Records Management is the “field of management responsible for the efficient and systematic control of the creation, receipt, maintenance, use, and disposition of records…” (ISO 15489). This course introduces the principles and practices involved in managing physical and digital records and information in private and public sector organizations. | MSIS/PhD |
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| INF 389G | Introduction to Electronic and Digital Records | MSIS/PhD | ||
| INF 389R | Introduction to Archival Enterprise I | MSIS/PhD | ||
| INF 389S | Introduction to Archival Enterprise II | This course will introduce students to contemporary issues in archival studies through readings, research, writing, group discussion, and visits from leaders in the archival studies field. | MSIS/PhD |
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| INF 390N | Information Policy | MSIS/PhD | ||
| INF 390N | Information Policy: Cybersecurity Law and Policy | MSIS/PhD | ||
| INF 390N | Information Policy: Communication Law and Policy | This course examines the U.S. communication policy in light of domestic and international structural, economic and technological changes. We will investigate how notions of control, access and expression have changed during the 20th and the 21st centuries, examining communication policies and regulation against a backdrop of technological innovation. The definitions and controversies around what constitutes the public interest intersect with policies for specific media systems including broadcasting, cablecasting, the Internet and social media, among others. The cultural ramifications of communication systems in terms of their impacts on people and on speech are a related domain we will address. At the current moment, issues around privacy, large tech companies and their role in contemporary life, the limits and authority of regulation, and of course social media,AI and ‘big data’ dominate many political and research agendas. Our goal will be to understand the backgrounds and foundations that bring us to these concerns and to frame them in critical ways. | MSIS/PhD |
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| INF 391D | Doctoral Inquiry in Information Studies | PhD Only | ||
| INF 391D.06 | Directed Readings | PhD Only | ||
| INF 391D.07 | Directed Research | PhD Only | ||
| INF 391D.10 | Survey of Information Studies | This course provides an overview of the major subject areas, ideas, concepts, and theories of Information Studies and introduces the basics of research, publication, and academic conventions in Information Studies. Prerequisites: Admission to the doctoral program and consent of the graduate advisor. | PhD Only |
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| INF 391D.11 | The Research Enterprise | PhD Only | ||
| INF 391D.12 | Disciplinary Foundations For Information Studies | PhD Only | ||
| INF 391F | Advanced Topics in Research Methods, Methodologies, and Design | PhD Only | ||
| INF 391F | Advanced Topics in Research Methods, Methodologies, and Design: Quantitative Research Methods | This course starts by discussing broad landscape of epistemological and theoretical perspectives and styles of reasoning and by situating in it quantitative research. It introduces you to the foundational concepts in quantitative research methods, such as causality, conceptualization, operationalization, measurement and sampling. It presents experimental design, survey design, and basic descriptive and inferential (frequentist) statistics, as well as a brief introduction to Bayesian inference and statistics. | PhD Only |
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| INF 391F | Advanced Topics in Research Methods, Methodologies, and Design: Qualitative Research Methods | PhD Only | ||
| INF 391G | Doctoral Writing Seminar | PhD Only | ||
| INF 392G | Management of Preservation Programs | Management of specific preservation strategies for the cultural record, with an emphasis on assessing preservation needs of a collection and grant writing. | MSIS/PhD |
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| INF 392K | Digital Archiving and Preservation | Examines the permanent archiving of digital information. Covers media refreshment, emulation, migration, and electronic records repository construction and administration. Case study projects involving campus repositories and off-campus institutions. Students use legacy hardware and software and digital forensics tools to preprocess digital collections for repository storage. Also explores issues in long-term electronic records preservation | MSIS/PhD |
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| INF 392L | Introduction to Audio Preservation and Reformatting | Study of audio recording through a chronological examination of the development of recording; basic care and preservation of recordings; Preservation of audio archives; and stability concerns of audiovisual media. | MSIS/PhD |
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| INF 393C | Conservation Laboratory Techniques | MSIS/PhD | ||
| INF 393C | Conservation Laboratory Techniques: Introduction to Paper Conservation | MSIS/PhD | ||
| INF 393C | Conservation Laboratory Techniques: Preservation Science and Practice | Ever wondered how libraries and archives safeguard historical materials for future generations? Preservation is the answer. In this course, students learn collections care strategies that enable today’s information stewards to protect our growing cultural record. Scientific foundations and practical exercises will address common preservation challenges, such as environmental control, mold, insects, pollutants, and light damage. Modern topics in health, safety, and sustainability will highlight the developing nature of the field. Students will evaluate preservation risks for books, paper, electronic media, and other collections materials. | MSIS/PhD |
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| INF 393C.11 | Treatment Techniques for Bound Materials | MSIS/PhD | ||
| INF 397 | Research in Information Studies | MSIS/PhD | ||
| INF 397 | Research in Information Studies: Data Management and the Research Life Cycle | MSIS/PhD | ||
| INF 397 | Research in Information Studies: Introduction to Machine Learning / Statistical Analysis and Learning | MSIS/PhD | ||
| INF 698A | Thesis | MSIS/PhD | ||
| INF 698B | Thesis | MSIS/PhD | ||
| ISP 398R | Master's Report | ISP | ||
| INF 398R | Master's Report | MSIS/PhD | ||
| INF 398T | Supervised Teaching in Information Studies | MSIS/PhD | ||
| INF 399W | Dissertation | MSIS/PhD | ||
| INF 699W | Dissertation | MSIS/PhD | ||
| INF 999W | Dissertation | MSIS/PhD | ||
| INF 398T | Supervised Teaching in Information Studies | MSIS/PhD | ||
| INF 399W | Dissertation | MSIS/PhD | ||
| INF 699W | Dissertation | MSIS/PhD | ||
| INF 999W | Dissertation | MSIS/PhD | ||
| Public Libraries | ||||
| Electronic Portfolio | ||||
| Advanced Usability | ||||
| Practicum in Research |