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.