Course Offerings

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.

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.

Survey the ethical foundations for informatics, incorporating non-Western and feminist perspectives. Apply these ethical foundations to contemporary problems in informatics. Examine the confrontation of ethical dilemmas in the workplace, including recognizing value trade-offs, affected stakeholders, and potential solutions. Offered on the letter-grade basis only. This course carries the Writing Flag and the Ethics flag Ethics courses are designed to equip students with skills that are necessary for making ethical decisions in their adult and professional lives. Students should therefore expect a substantial portion of their grade to come from assignments involving ethical issues and the process of applying ethical reasoning to real-life situations.

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.

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.

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.

No description provided.

Develop familiarity with diverse research approaches to investigate informatics-related problems. Learn principles and hands-on practices of data collection and analysis with respect to qualitative, quantitative, and mixed research methods. *Temporarily placeholder course only offered once in Spring 2022. Superseded by I 305 Research Methods for Informatics as of Fall 2022.

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.

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.

Explore the leveraging of data, information, and technology for the greater benefit of society and to help ensure a level playing field for everyone in the information age. Offered on the letter-grade basis only. This course carries the Cultural Diversity in the United States flag. The purpose of the Cultural Diversity in the United States Flag is for students to explore in-depth the shared practices and beliefs of one or more underrepresented cultural groups subject to persistent marginalization. In addition to learning about these diverse groups in relation to their specific contexts, you’ll also reflect on your own cultural experiences.

Explore designing and implementing information technologies to improve healthcare delivery, healthcare management, and health outcomes. Offered on the letter-grade basis only.

An introduction to sociotechnical perspectives on information systems, their effects, and how we intervene to make them better.

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.

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.

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.

Built on the back of a blockchain computing stack, this course will focus on topics and research key to the transition to Web 3 and a decentralized economy. We will cover the dynamics of blockchain technology, highlight new ideas from leading entrepreneurs and researchers shaping this future, and provide students with an opportunity to build their research into a product or startup. Students will use lean methodologies and anchor their approach in content covered through the course.

The goal of this course is to help develop practical design and research skills while learning about the many facets of healthcare.

Design and research fundamentals covers what it means to apply research and design to problems faced by consumers, businesses, and groups of people. The techniques covered in this course will help students gain confidence in visual communication, understand the different practices related to learning about users, and the elements of design.

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.

No description provided.

Engage in modern ethical dilemmas within archives, libraries, and museums, considering issues of collections management and preservation within changing cultural frameworks. This I 320C topic carries the Cultural Diversity in the United States flag. The purpose of the Cultural Diversity in the United States Flag is for students to explore in-depth the shared practices and beliefs of one or more underrepresented cultural groups subject to persistent marginalization. In addition to learning about these diverse groups in relation to their specific contexts, you’ll also reflect on your own cultural experiences.

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?

No description provided.

The class explores the principles of relational database design, and SQL as a query language in depth.

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

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).

Practical skills and understandings required to effectively work with open source software and understand the projects that build them. Includes git-based collaboration as well as conceptual understanding of licenses, security, technical and social processes in open source development. Class projects involve working with digital trace data from open source repositories.

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.

Introduction to the emerging field of Explainable Artificial Intelligence (XAI) from the perspectives of a developer and end-user. Students will gain hands-on experience with some of the most commonly used explainability techniques and algorithms.

Leveraging Text Mining, Natural Language Processing, and Computational Linguistics to address real-world textual data challenges, including document processing, keyword extraction, question answering, translation, summarization, sentiment analysis, search, recommendation, and information extraction. Each week, classes include (a) Theory and Methods for NLP concepts and (b) Lab Tutorials for practical application with Python on multilingual text datasets.

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.

Provides students with an understanding of the fundamental concepts, common methods, and analytical tools of social network analysis. Students will gain experience applying both exploratory and qualitative methods to real-world problems within the social network domain.

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.

*THIS TOPIC WILL NO LONGER BE OFFERED AFTER SPRING 2025In 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.

Critical exploration of the intersection between digital technologies and information access in emerging economies. Investigate the historical, socio-economic, and ethical dimensions of digital adoption in the Global South, analyzing its impact on governance, economies, cultures, and societal dynamics. Emphasis on critical thinking, ethical considerations, and collaborative approaches to address challenges such as the digital divide(s), data sovereignty, and technology-driven inequality. Through case studies and practical exercises, students will develop skills in digital research, global cultures, policy analysis, and technology innovation with a focus on promoting inclusive and sustainable digital transformation in Global South contexts. Also offered as I 320S.

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.

No description provided.

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.

Project-based learning course in which students will apply a combination of research and evaluation methods (scientific, sociological, historical, computational) to identify and explore a research question of community impact. Students will first learn about applied research and evaluation from a team of faculty and community-based nonprofit leaders, then work in small groups apply their knowledge.

No description provided.

Overview of public health and the information systems used to achieve public health goals. This course is divided into three parts: (1) overview of public health, (2) fundamentals of public health informatics, and (3) public health information systems.

Leveraging medical claims data to guide population health interventions, primarily through the use of machine learning models. The course will focus on the data processing pipeline, and no prerequisite knowledge of machine learning models is required

Explore principles and methodologies in health informatics research, including various approaches to data analysis, research design, and the application of informatics to health. Develop skills in reading, reviewing, and writing scientific publications, identifying research questions, initiating research, and communicating findings.

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.

New Topic for Spring 2025. Description pending submission by instructor, Steve Hershman. Also offered as Informatics 320D.

No description provided.

Online communities are important to our cultural, social, and economic lives and especially to how we find and share information. Yet they also threaten our well-being and may undermine critical social institutions as well as the integrity of public discourse. This course is an interdisciplinary inquiry that seeks to understand online communities. It covers the history of online communities from their origins in the pre-Internet to the rise of social media platforms and contemporary challenges and also the social, psychological, and human-computer interaction research that both explains the practical barriers to building an online community and motivates technical and organizational designs that aim to overcome them.

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.

Critical exploration of the intersection between digital technologies and information access in emerging economies. Investigate the historical, socio-economic, and ethical dimensions of digital adoption in the Global South, analyzing its impact on governance, economies, cultures, and societal dynamics. Emphasis on critical thinking, ethical considerations, and collaborative approaches to address challenges such as the digital divide(s), data sovereignty, and technology-driven inequality. Through case studies and practical exercises, students will develop skills in digital research, global cultures, policy analysis, and technology innovation with a focus on promoting inclusive and sustainable digital transformation in Global South contexts. Also offered as I 320J.

Practical skills and understandings required to effectively work with open source software and understand the projects that build them. Includes git-based collaboration as well as conceptual understanding of licenses, security, technical and social processes in open source development. Class projects involve working with digital trace data from open source repositories. Also offered as Informatics 320D.

No description provided.

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.

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.

Effective application of social and technical methods of analysis to specific existing systems with inseparable technical and social components to enable improvement. Covers techniques such as modeling, interviewing, observation, trace analysis, and benchmarking.

No description provided.

*THIS TOPIC WILL NO LONGER BE OFFERED AFTER SPRING 2025In 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.

Develop fundamental graphic design theory and skills to prepare students for careers in Informatics and related fields.

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.

This course focuses on the unique design practice of (1) representing and organizing information to facilitate perception and understanding (information architecture) and (2) specifying the appropriate mechanisms for accessing and manipulating task and play information (interaction design). This course also explores design patterns appropriate for the HCI professional.

Examine social and psychological experiences of virtual environments and immersive technologies, such as in virtual reality and augmented reality. Through the course students will learn about the immersive technology and the research behind people’s experiences of virtual environments.

Digital Accessibility has become a critical topic for product leaders, developers, UX designers, and usability researchers. This course will explore the legal, ethical, and practical aspects of Accessibility as it relates to creating inclusive products and experiences for persons with disabilities. While Accessibility applies to both the physical and digital world, a large portion of the course will be focused on digital experiences, and those that combine technology with devices and tools.

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.

Introduction to the methodologies and techniques required for designing an ideal user experience with physical objects. Students will use qualitative, quantitative, and anthropometric data to design and iterate projects.

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.

Online communities are important to our cultural, social, and economic lives and especially to how we find and share information. Yet they also threaten our well-being and may undermine critical social institutions as well as the integrity of public discourse. This course is an interdisciplinary inquiry that seeks to understand online communities. It covers the history of online communities from their origins in the pre-Internet to the rise of social media platforms and contemporary challenges and also the social, psychological, and human-computer interaction research that both explains the practical barriers to building an online community and motivates technical and organizational designs that aim to overcome them.

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

Student works independently to accomplish an approved objective under the guidance of a member of the iSchool faculty, or an adjunct instructor approved by the Undergraduate Program Coordinator. To enroll in this course, students must submit an approved Independent Study Proposal to the iSchool undergraduate student services office during an active registration period.

Student works independently to accomplish an approved objective under the guidance of a member of the iSchool faculty, or an adjunct instructor approved by the Undergraduate Program Coordinator. To enroll in this course, students must submit an approved Independent Study Proposal to the iSchool undergraduate student services office during an active registration period.

Student works independently to accomplish an approved objective under the guidance of a member of the iSchool faculty, or an adjunct instructor approved by the Undergraduate Program Coordinator. To enroll in this course, students must submit an approved Independent Study Proposal to the iSchool undergraduate student services office during an active registration period.

Student assists and collaborates with a member of the iSchool’s full time research faculty on a project directly supporting their academic research. To enroll in this course, students must submit an approved Research Experience Proposal to the iSchool undergraduate student services office during an active registration period.

Student assists and collaborates with a member of the iSchool’s full time research faculty on a project directly supporting their academic research. To enroll in this course, students must submit an approved Research Experience Proposal to the iSchool undergraduate student services office during an active registration period.

Student assists and collaborates with a member of the iSchool’s full time research faculty on a project directly supporting their academic research. To enroll in this course, students must submit an approved Research Experience Proposal to the iSchool undergraduate student services office during an active registration period.

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.

Research, read, and develop an honors thesis subject and proposal for one semester; followed in the second semester by the writing and defense of a final honors thesis. Two-semester course taken as I 679HA (semester 1) and I 679HB (semester 2). Credit will be awarded upon completion of both semesters. This course has been approved by Undergraduate Studies to award the Independent Inquiry Flag and theWriting Flag. Interested students should speak with their advisor and submit an approved Informatics Honors Thesis Proposal prior to registration.

Research, read, and develop an honors thesis subject and proposal for one semester; followed in the second semester by the writing and defense of a final honors thesis. Two-semester course taken as I 679HA (semester 1) and I 679HB (semester 2). Credit will be awarded upon completion of both semesters. This course has been approved by Undergraduate Studies to award the Writing Flag. Interested students should speak with their advisor and submit an approved Informatics Honors Thesis Proposal prior to registration.

Explore foundational concepts of information security and privacy, including information value, classifications, threats, liabilities and risk management, identity and access controls (IAM), trust frameworks, technology for network, web, software and cloud security; and privacy laws and regulations.

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.

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.

In-depth study of a problem or topic related to information studies, usually culminating in an examination or a scholarly written report. Individual Instruction. With the consent of the graduate advisor, may be repeated for credit. INF 181 is worth 1 hour of semester credit. Students wanting 2 or 3 hours of credit should take INF 281 or INF 381 respectively. Individual Study registration/proposal form

In-depth study of a problem or topic related to information studies, usually culminating in an examination or a scholarly written report. Individual Instruction. With consent of the graduate advisor, may be repeated for credit. INF 281 is worth 2 hours of semester credit. Students wanting 1 or 3 hours of credit should take INF 181 or INF 381 respectively. Individual Study registration/proposal form

Examine how information is socially and culturally variable and fluid, changing throughout history and differing from place to place. Explore the anthropological study of information; societal norms; and individual, device, communal, and organizational information strategies.

In-depth study of a problem or topic related to information studies, usually culminating in an examination or a scholarly written report. Individual Instruction. With consent of the graduate advisor, may be repeated for credit. INF 381 is worth 3 hours of semester credit. Students wanting 2 or 3 hours of credit should take INF 281 or INF 381 respectively. Individual Study registration/proposal form

Explore an overview of how information and public policy relate to each other. Examine key information policy areas including privacy, surveillance, theft, health information, business-to-business relationships, and the co-evolution of personal data and information technologies.

Explore an overview of how information and public policy relate to each other. Examine key information policy areas including privacy, surveillance, theft, health information, business-to-business relationships, and the co-evolution of personal data and information technologies.

Major reference resources and strategies useful in providing information services in libraries and other information agencies.

Major reference resources and strategies useful in providing information services in libraries and other information agencies.

Examines the evaluation, selection, and use of books and other media for young adults of junior and senior high school age. Briefly surveys the reading experience, psychology of adolescence, and reading interests of young adults. Includes extensive reading and viewing. May be repeated for credit when the topics vary.

Explore the evaluation, selection, and use of books and other media and materials to meet the needs of children and young adults.

Evaluation and use of printed online information resources and services in specialized areas, with emphasis on new information technologies. Information-seeking behavior of users, document delivery, new roles of the information specialist in user support, and information needs of a variety of clients. May be repeated for credit when the topics vary.

Evaluation and use of printed online information resources and services in specialized areas, with emphasis on new information technologies. Information-seeking behavior of users, document delivery, new roles of the information specialist in user support, and information needs of a variety of clients. May be repeated for credit when the topics vary.

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.

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.

Explore an organizational perspective on the management and governance of information. Examine business practices and governance mechanisms for minimizing risks and maximizing returns of information.

Explore an organizational perspective on the management and governance of information. Examine business practices and governance mechanisms for minimizing risks and maximizing returns of information.

Explore framing messages and the impact on people, organizations, risks and privacy; effective crisis management communications; communication and business continuity planning; time management; sense making processes in organizational crisis; and reputation management.

Explore framing messages and the impact on people, organizations, risks and privacy; effective crisis management communications; communication and business continuity planning; time management; sense making processes in organizational crisis; and reputation management.

Introduction to the concepts of information organization, representation, and classification. Consideration of different traditions of practice and user concerns.

Philosophical and social context, objectives, and methodology of evaluating, selecting, and managing library materials.

The science and engineering of building automated search engines: foundations and emerging methods, key models and approaches, front-end usability and back-end algorithms, theories of relevance, annotation practices, and system evaluation/benchmarking.

Principles and practices for describing information resources.

Explore and evaluate the risks and benefits related to information in multiple sectors including financial services, healthcare, consumer services, government, education, and energy.

Explore and evaluate the risks and benefits related to information in multiple sectors including financial services, healthcare, consumer services, government, education, and energy.

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.

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.

Designed to build upon the skills covered in Information Studies 385P. Individual project evaluating a Web site or other software user interface. Students devise a plan for testing, secure IRB approval to test human subjects, conduct study, analyze date, write a report, and present the results and conclusions.

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

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

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.

Study the characteristics of information and the technologies, stakeholders, and questions involved in managing, protecting, and securing information.

No description provided.

Study the characteristics of information and the technologies, stakeholders, and questions involved in managing, protecting, and securing information.

No description provided.

Exploration of major components of health IT systems, ranging from data semantics (ICD10), data interoperability (FHIR), diagnosis code (SNOMED CT), to workflow in clinical decision support systems. After establishing a good understanding of the fundamentals of health IT systems, we will dive deep into how AI innovations (e.g., machine learning, deep learning, computer vision) are transforming our healthcare system by introducing new concepts of mobile health, AI diagnosis, AI medicine, smart device, and intelligent delivery.

Introduction to structures and practices within the rapidly-evolving field of librarianship. prepares students for their graduate work here.

A practical introduction and guide for using statistics to solve quantitative problems in user research. Many designers and user researchers view usability and user research as qualitative activities, which do not use formulas and numbers. However, usability practitioners and user researchers are increasingly expected to quantify the benefits of their efforts. The impact of good and bad designs can be quantified in terms of user performance, task completion rates and times, perceived user satisfaction. The course will address questions frequently faced by user researchers, such as, how to compare usability of products for A/B testing and competitive analysis, how to measure the interaction behavior and attitudes of users, how to estimate the number of users needed for usability testing. The course will introduce students to a foundation for statistical theories and the best practices needed to apply them. It will cover descriptive statistics, confidence intervals, standardized usability questionnaires, correlation, regression, and analysis of variance. It will also address how to effectively communicate the quantitative results.

Build awareness of the Product Management practice, surface shared goals and processes between PM and UX, highlight possible areas of conflict, and discover approaches to forming an effective collaborative relationship.

Explore hypothesis generation, design and set up of experiments (AB tests), quasi-experimental methods (regression, matching, heterogeneous treatment effects, etc.), interpreting results and uncertainty, and communicating insights to various audiences; with a focus on impacting practical business and product decisions.

Explore hypothesis generation, design and set up of experiments (AB tests), quasi-experimental methods (regression, matching, heterogeneous treatment effects, etc.), interpreting results and uncertainty, and communicating insights to various audiences; with a focus on impacting practical business and product decisions.

The course provides students with an overview of topics related to child development and user interface design for children, with an emphasis on early and middle childhood. Through this course students will learn about technology’s potential impact on cognitive and social development and how child development relates to media design. Students will interact and evaluate digital media technologies on children’s learning, including social learning. Topics include, but are not limited to, brain development, social cognition, symbolic processing, media usage, and self-representation.

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.

The emphasis of this course will focus on how to be successful in a UX career in a corporate setting, focusing on hardware product design. Students will become familiar with product development phase gates leading up to a product's launch, and what UX methodologies might be most useful to employ at each phase. In order to build cross-functional empathy, we will explore the roles of the extended product team players (e.g. Architecture, Marketing, Engineering, Program Management, Product Management, Industrial Design, Interaction Design, etc.) and discuss when to engage with them and how. We will also explore how to align design recommendations with a company's financial goals by touching on how to read a company's quarterly report, prioritizing UX requirements through a fiscally responsible lens, and business case development. My goal for this course is that students come away with skills that will equip them with awareness of each corporate function's lingo ("talk the talk") and modus operandi ("walk the walk"), such that they can successfully ensure the adoption of their UX designs and recommendations. Implementing what we learn will also forge strong rapport and relationships with other product team counterparts. This rapport will pay off future dividends and help differentiate ourselves from others in our discipline, building a strong foundation from which to launch a fruitful UX career.

The emphasis of this course will focus on how to be successful in a UX career in a corporate setting, focusing on hardware product design. Students will become familiar with product development phase gates leading up to a product's launch, and what UX methodologies might be most useful to employ at each phase. In order to build cross-functional empathy, we will explore the roles of the extended product team players (e.g. Architecture, Marketing, Engineering, Program Management, Product Management, Industrial Design, Interaction Design, etc.) and discuss when to engage with them and how. We will also explore how to align design recommendations with a company's financial goals by touching on how to read a company's quarterly report, prioritizing UX requirements through a fiscally responsible lens, and business case development. My goal for this course is that students come away with skills that will equip them with awareness of each corporate function's lingo ("talk the talk") and modus operandi ("walk the walk"), such that they can successfully ensure the adoption of their UX designs and recommendations. Implementing what we learn will also forge strong rapport and relationships with other product team counterparts. This rapport will pay off future dividends and help differentiate ourselves from others in our discipline, building a strong foundation from which to launch a fruitful UX career.

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.

Develop prompts for text and image generation through an iterative cycle, making the most of foundation models, including large language models and diffusion models. Overview of the field of prompt engineering, including historical development, ethical dilemmas, and the creation of chatbots.

Develop prompts for text and image generation through an iterative cycle, making the most of foundation models, including large language models and diffusion models. Overview of the field of prompt engineering, including historical development, ethical dilemmas, and the creation of chatbots.

This course introduces students to the critical study of data through the landscape of networked information and communication technologies (ICTs)—their history, present, and future. It will examine the social impact and technical developments of data technologies, defined as any system designed to gather, process, or distribute information and data through network architecture.

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.

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.

Introduction to Explainable AI through practical applications and real-world examples. Students will gain a basic proficiency in implementing Explainer Algorithms to explain the decisions of ML and AI systems, as well as interpreting the results in a transparent and understandable manner to a non-technical audience. The course will focus on Post-Hoc Explainability techniques and algorithms, including Feature Attribution, Rule-Based and Counterfactuals. Another focus area will be on evaluating the performance of explainability techniques, and understanding the trade-offs associated with various methods. This course is geared towards students interested in a hands-on approach to developing explanations for black-box ML and AI Systems.

Introduction to digital forensic technology, computer network security, and organizational planning and response to cyberattacks.

Introduction to tools and methods, software and hardware, to produce physical information displays.

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.

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.

Ethical challenges related to AI and how to address them. Introduces a broad range of ethical theories, including non-Western and feminist theories, and applies them to contemporary ethical challenges resulting from AI.

Ethical challenges related to AI and how to address them. Introduces a broad range of ethical theories, including non-Western and feminist theories, and applies them to contemporary ethical challenges resulting from AI.

Examine people’s social and psychological experiences of virtual environments, such as in virtual reality. Students will learn about the research behind people’s experiences of virtual environments.

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

*THIS TOPIC WILL NO LONGER BE OFFERED AFTER SPRING 2025In 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.

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.

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.

Introduction to basic design concepts such as composition, color theory, interactions; the Lean UX methodology, history, predecessor, pros/cons, and adaptations on Lean UX and case studies from companies such as Google; application of rapid prototyping using the latest design tools and methods.

Explore the theories and applications of surveillance and the impacts both have had on society and culture, over time and geography, including the application of technology. Examine how we participate in these systems as subjects, performers, and watchers in our own right, and how individuals can take more control over the processes of surveillance in their lives.

Explore the potential value that post-positivist research perspectives bring to critically examining issues like digital exclusion that are prefigured by underlying systemic/structural inequities. Students will also learn how philanthropic grantmaking programs can be designed to support solutions to root causes that issues like digital inequality reveal to us.

Introduction to the computational skills needed to conduct digital text analysis using the R programming language. The analytical activities thus covered include text mining as well as statistics, predictive modeling, content modeling, sentiment analysis, and more.

Introduction to the computational skills needed to conduct digital text analysis using the R programming language. The analytical activities thus covered include text mining as well as statistics, predictive modeling, content modeling, sentiment analysis, and more.

Explores the role of library and information organizations in communities, with a focus on building community relationships, engagement, and outreach.

Examination of propaganda and disinformation campaigns, the psychology behind how they work and how they became central to both the Cold War and political elections; as well as the advent of social media and algorithmic optimization to facilitate and accelerate the reach and impact.

Examination of propaganda and disinformation campaigns, the psychology behind how they work and how they became central to both the Cold War and political elections; as well as the advent of social media and algorithmic optimization to facilitate and accelerate the reach and impact.

Introduction to product and project management concepts as a foundation for UX, library sciences and other related fields.

Introduction into the discipline and industry of information security (also known as cyber security). We will explore the history, theory, and practices of how we protect and control information in a connected, digital world. Information security is a complex topic that has become highly technical and specialized, and this course is designed to serve students regardless of their technical background or proficiency

Structured to deliver open Internet services, and a new kind of software architecture, Web3 (and its native crypto-assets) is poised to answer the original vision of the Internet, built on the back of a blockchain computing stack. Students will hear from leading entrepreneurs, produce weekly assignments, and ultimately build toward a final research paper on a relevant Web3 topic.

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.

Structured to deliver open Internet services, and a new kind of software architecture, Web3 (and its native crypto-assets) is poised to answer the original vision of the Internet, built on the back of a blockchain computing stack. Students will hear from leading entrepreneurs, produce weekly assignments, and ultimately build toward a final research paper on a relevant Web3 topic.

Processes, techniques, and technologies that generate inscriptions (ready-to-take data), especially from or about people(s) or culture(s). Contexts, consequences, and history of datafication practices. Purposive intervention with datafication processes, practices, and artifacts.

Recently Deep Learning (DL) techniques have shown a lot of promise for tasks in various modalities such as speech, language, and vision and DL has become a go-to machine learning paradigm for Artificial Intelligence (AI) based applications. The course aims to cover theoretical and applied aspects of Deep Learning and how it is used to solve real-world problems. Classes in each week may be divided into two segments: (a) Theory and Methods, a concise description of a deep learning algorithm, and (b) Lab Tutorial, a hands-on session on applying the algorithm on multimodal real world data such as textual, visual and audio data.

Processes, techniques, and technologies that generate inscriptions (ready-to-take data), especially from or about people(s) or culture(s). Contexts, consequences, and history of datafication practices. Purposive intervention with datafication processes, practices, and artifacts.

This course provides the knowledge and skills required to develop an accessible and user-friendly web application from start to finish. Students will learn to apply accessibility and heuristic principles when developing a web application to deliver the best experience to end-users.

Computer vision is a field of artificial intelligence (AI) that enables computing systems to extract meaningful information from digital images, videos, and other visual inputs to make computable decisions. The camera captures digital photos and videos, and algorithms process and derive valuable information, which can help in making better decisions and recommendations. This course offers a comprehensive review of computer vision emphasizing its fundamental principles and their applicability in the real world, from fashion to deep face recognition.

Academic and research oriented introduction to computational methods from a social science research design perspective.

Foundations of evaluation, including using the logic model, program evaluation, data gathering, analysis and reporting. Examples of evaluation and assessment in public, academic, and special are explored, with an emphasis on how libraries use data and evaluation to inform decision-making and support advocacy.

Academic and research oriented introduction to computational methods from a social science research design perspective.

Explores the role of library and information organizations in communities, with a focus on building community relationships, engagement, and outreach.

Visual, numerical, textual, and verbal presentation of information based on fundamental theories of human information perception and communication. Examples may include tables, graphs, dashboards, infographics, and reports.

Mapping for the Common Good provides students of any background and any academic specialty/interest a broad theoretical and technical understanding of maps, spatial data and geovisualization. It is intentionally structured to highlight the many ways in which geographic information technologies and spatial reasoning skills can profoundly impact our understanding of the world. It also provides students with an opportunity to better appreciate how spatial data and mapping can be used to develop strategies, plans, and designs to improve the quality of life for communities and their citizens.

Visual, numerical, textual, and verbal presentation of information based on fundamental theories of human information perception and communication. Examples may include tables, graphs, dashboards, infographics, and reports.

Examine the opportunities and challenges for using crowdsourcing to teach computers to "see".

Introduction to the theory, methods, and applications of human computation and crowdsourcing; covering a breadth of key concepts as well as more specialized depth in one or more key sub-areas.

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.

Introduction to combining human and machine intelligence to benefit people and society. Explore cutting-edge research on a number of subjects related to human-AI interaction, including the psychological and societal impacts of AI as well as design guidelines and methods for human-centered AI.

Introduction to health informatics; includes fundamentals of information in biomedicine, nursing, public health, bioinformatics and genomics, electronic records, and integrated systems.

Explore the enrollment and authentication for cyber and physical access and transactions, cryptography, biometrics, device identity security, and security culture.

Introduction to health informatics; includes fundamentals of information in biomedicine, nursing, public health, bioinformatics and genomics, electronic records, and integrated systems.

Explore the enrollment and authentication for cyber and physical access and transactions, cryptography, biometrics, device identity security, and security culture.

A survey of the history of information, with a focus on information professions and centers (e.g. libraries, archives, schools, museums, newspapers, social media, non-profit/for-profit corporations, government settings, etc.) in the United States over the last 150 years. Interdisciplinary examination of 'information' and its manifestations in historical but also philosophical, sociological, political, economic, journalistic, and technological contexts.

Examines information as a cultural phenomenon; may include e-commerce, privacy and secrecy, censorship, information as a commodity, Internet culture, access to cultural heritage, and control of the cultural record. Repeatable with Different Topics

Explore knowledge and data management, storage, and mining. Examine information representation and algorithms. Discuss information security and privacy applications in all market sectors for enrollment, authentication, operational use, fraud detection, and fraud prevention.

Examines information as a cultural phenomenon; may include e-commerce, privacy and secrecy, censorship, information as a commodity, Internet culture, access to cultural heritage, and control of the cultural record. Repeatable with Different Topics

Explore knowledge and data management, storage, and mining. Examine information representation and algorithms. Discuss information security and privacy applications in all market sectors for enrollment, authentication, operational use, fraud detection, and fraud prevention.

Theory and practice in the design, behavior, evaluation, and administration of libraries and other information agencies and systems. Marketing of information organizations and resources. Administrative applications of technology. May be repeated for credit when the topics vary.

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.

Examine laws and other policy instruments related to information security and privacy, different classes of protected personal information, and multiple genres of legal information and legal writing. Explore legal requirements and social responsibilities as they pertain to data protection and the prevention of different types of fraud and information crimes.

The process of exhibit creation in historical museums, from planning through development to opening and maintenance, as a negotiation among stakeholders for influence on the story that is told. Students visit local historical museums and examine how presentations are influenced by the institutional position of the museum, including its history and resources; the concerns of museum employees; the influence of the audience and of those who are directly affected or represented by an exhibit; and the role of contractual professionals.

Examine laws and other policy instruments related to information security and privacy, different classes of protected personal information, and multiple genres of legal information and legal writing. Explore legal requirements and social responsibilities as they pertain to data protection and the prevention of different types of fraud and information crimes.

The process of exhibit creation in historical museums, from planning through development to opening and maintenance, as a negotiation among stakeholders for influence on the story that is told. Students visit local historical museums and examine how presentations are influenced by the institutional position of the museum, including its history and resources; the concerns of museum employees; the influence of the audience and of those who are directly affected or represented by an exhibit; and the role of contractual professionals.

History, missions, values, governance, funding, services, user communities, architecture, leadership, and issues in public librarianship.

Study practical problems, current phenomenon, or professional issues in an institutional setting.

Minimum 80 hours of supervised fieldwork for one semester. For each semester hour of credit earned, the equivalent of one lecture hour a week for one semester, with additional hours to be arranged. Offered on the credit/no credit basis only. May not be counted toward any degree in the School of Information. Required Form: https://www.ischool.utexas.edu/sites/default/files/images/iSchool_x88T_…

Supervised fieldwork. Minimum 125 hours of supervised fieldwork for one semester. Offered on the credit/no credit basis only. May not be counted toward any degree in the School of Information. Required Form: https://www.ischool.utexas.edu/sites/default/files/images/iSchool_x88T_…

In-depth study of a problem or topic related to Information Security and Privacy. Individual Instruction. May be repeated for credit. ISP 189 is worth 1 hour of semester credit. Students wanting 2 or 3 hours of credit should take ISP 289 or INF 389 respectively.

In-depth study of a problem or topic related to Information Security and Privacy. Individual Instruction. May be repeated for credit. ISP 289 is worth 2 hours of semester credit. Students wanting 1 or 3 hours of credit should take ISP 189 or INF 389 respectively.

In-depth study of a problem or topic related to Information Security and Privacy. Individual Instruction. May be repeated for credit. ISP 389 is worth 3 hours of semester credit. Students wanting 1 or 2 hours of credit should take ISP 189 or INF 289 respectively.

In-depth study of a problem or topic related to Information Security and Privacy. Individual Instruction. May be repeated for credit. ISP 189 is worth 1 hour of semester credit. Students wanting 2 or 3 hours of credit should take ISP 289 or INF 389 respectively.

In-depth study of a problem or topic related to Information Security and Privacy. Individual Instruction. May be repeated for credit. ISP 289 is worth 2 hours of semester credit. Students wanting 1 or 3 hours of credit should take ISP 189 or INF 389 respectively.

In-depth study of a problem or topic related to Information Security and Privacy. Individual Instruction. May be repeated for credit. ISP 389 is worth 3 hours of semester credit. Students wanting 1 or 2 hours of credit should take ISP 189 or INF 289 respectively.

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.

Examines personal recordkeeping and information management to explore the creation, management, and preservation of digital information. Includes current developments in digital technology that affect recordkeeping.

Introduction to the records aspect of archival enterprise, from acquisition to use, with emphasis on arrangement and description.

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.

Critical examination of conflicts and trends in information policy in private organizations and in federal, state, and international public-sector organizations. Repeatable with Different Topics

A deep dive into a broad range of legal and policy issues associated with cybersecurity, intended as a comprehensive introduction to the topic and the many public and private institutions involved in it. See instructor's previous syllabus sample.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

Topics in the theoretical, methodological, and practical aspects of information studies. Repeatable with Different Topics.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

No description provided.

An overview of the nature and purposes of research, and common methods and methodologies in information studies.

An overview of concepts, results, and perspectives from philosophical, social science, humanistic, design, and technological disciplines that provide important underpinnings for information studies.

No description provided.

Management of specific preservation strategies for the cultural record, with an emphasis on assessing preservation needs of a collection and grant writing.

Explores a variety of approaches to qualitative methods including ethnography, participant observation, case studies, grounded theory, phenomenology, action research, and so forth. Students will have a hands-on opportunity to conduct their own research project in which they will learn, discuss, and reflect upon the procedures of qualitative research.

Intensive writing, critique, and rewriting to assist senior doctoral students with refining their research writing in preparation for qualifying papers, dissertation proposals, and formal publications. May be repeated for credit.

Analysis, housing, and treatment of physical objects. Repeatable with Different Topics

Introduction to the ethical principles of conservation; conservation documentation; and hands-on treatment techniques for prolonging the lifetime of cultural materials.

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.

Analysis, housing, and treatment of physical objects. Repeatable with Different Topics

Introduction to the ethical principles of conservation; conservation documentation; and hands-on treatment techniques for prolonging the lifetime of cultural materials.

This class equips thoughtful thinkers with powerful data science skills. You will learn how to manage and work with complex and big datasets in social science research, particularly in policy and nonprofit studies. You are expected to learn the following skills and respond to "big questions" that have social importance: 1) Understand the structure of data and how to work with big and complex datasets; 2) Understand the workflows of acquiring and managing data; 3) Able to conduct data-intensive and replicable social science research. *NOTE: In previous years, this topic was offered as INF 385T. These classes are identical, and students may not receive credit for both versions.

Basic techniques for care and handling of bound materials including but not limited to sewing structure, minor mends, and enclosures.

Methods and subjects of research in information studies. Repeatable with Different Topics NOTE: MSIS students must earn a grade of B or better in the MSIS core courses (below) in order for the courses to apply to the master's degree. A grade of B- does NOT satisfy this requirement.

This class equips thoughtful thinkers with powerful data science skills. You will learn how to manage and work with complex and big datasets in social science research, particularly in policy and nonprofit studies. You are expected to learn the following skills and respond to "big questions" that have social importance: 1) Understand the structure of data and how to work with big and complex datasets; 2) Understand the workflows of acquiring and managing data; 3) Able to conduct data-intensive and replicable social science research. *NOTE: In previous years, this topic was offered as INF 385T. These classes are identical, and students may not receive credit for both versions.

Preparation of a report to fulfill the requirement for the master's degree under the report option.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the graduate coordinator for registration.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the graduate coordinator for registration. Offered on the credit/no credit basis only. Please refer to the iSchool Capstone Handbook for instructions on how to register for the Master's Thesis. NOTE: All Capstone courses require student participation in an end-of-semester poster session. Please see poster session guidelines at http://www.ischool.utexas.edu/programs/masters/capstone/poster_session_… for further information.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the graduate coordinator for registration. INF 698B can only be taken immediately after completion of INF 698A. To register, please contact the iSchool Course Administrator. Offered on the credit/no credit basis only. NOTE: Besides working with their individual Faculty Supervisors, students must also contact the instructors of INF 388L/R in order to attend aggregated Capstone class meetings during the times currently scheduled for INF 388L/R. All Capstone courses require student participation in an end-of-semester poster session.

Writing of the dissertation. The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the graduate coordinator for registration. May be repeated for credit. Offered on the credit/no credit basis only.

Writing of the dissertation. The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the graduate coordinator for registration. May be repeated for credit. Offered on the credit/no credit basis only.

No description provided.

No description provided.

No description provided.

No description provided.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

Examine theory and practical applications of data and artificial intelligence governance related to information security, privacy, compliance, and ethics. Explore optimization of technical and human dimensions for information risk management. Explore pervasive and emerging risks, risk assessments of data architectures and analytics, and regulations, controls, and governance to protect and safeguard information assets.

Examine established and emerging laws and public policy related to information security and privacy. Examine different classes of protected information and case studies documenting compliance and violation of legal and public policy protections. Explore legal requirements, corporate responsibilities and social responsibilities as they pertain to data protection and the prevention of different types of fraud and information crimes.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

The individual student works under supervision of a member of the graduate faculty. Students must present the faculty member's name to the iSchool Registration/Course Administrator for registration.

Analyze social and cultural issues related to communications technology systems.