Course Offerings

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

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

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.

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.

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.

No description provided.

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.

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

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

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

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.

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.

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.

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_…

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.

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

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.

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.

Analyze social and cultural issues related to communications technology systems.