Exploration of a topic (to be determined) not covered by the standard curriculum but of interest to faculty and students in a particular semester.

Survey of the professional, social, ethical, and legal issues affecting information service professionals and organizations and prepares students to deal with these issues and work with a diverse community.

Provides students on K-12, public, and academic library paths with context, awareness, and strategies to develop programs, services and facilities, and to select resources and technologies that ensure patrons and staff with disabilities have inclusive library experiences.

Offered through SUAbroad by educational institution outside the United States. Student registers for the course at the foreign institution and is graded according to that institution's practice. SUAbroad works with the S.U. academic department to assign the appropriate course level, title, and grade for the student's transcript.

Exploration of a topic (to be determined) not covered by the standard curriculum but of interest to faculty and students in a particular semester.

Topics include the basic concepts, ethics/codes, procedures, forensic techniques, analysis, example cases, hands-on labs, and applications to existing environments such as e-mail, social media, mobile devices, IoT, and others. Additional work required of graduate students.

History, theories, standards, and practices of bibliographic control of information resources with a focus on the library community. Practice creating original bibliographic and authority records and adapting, editing existing records using various technologies and tools, and applying subject vocabularies and classification systems.

Equips students with foundational knowledge of library ethics/standards, user information behavior, information literacy (including core information search, evaluation, and use practices), library resource types and discovery tools, question answering strategies, and related user-responsive library resources and services.

Introduction to Digital Humanities (DH) in Libraries, Archives, Museums, and other cultural institutions, with a focus on how information professionals can make use of DH methods and approaches and support and sustain DH work in their communities.

Students complete distributed ledger labs before developing, implementing, and 'demo or die' sharktanking their own new blockchain project. Blockchain concepts such as decentralization, smart contracts, trust and consensus governance are discussed. Additional work for graduate students. 

Information and communication technologies for teaching and learning in all types of libraries: practice with tools along with consideration of pedagogy (instructional design and evaluation of tools for learning objectives) and context (ethics, policies, legislation).

Introduction to best practices and methods to support and develop youth services programming in school and public library settings. Students gain skills in collection development, knowledge of youth literature, and information literacy instruction to serve a rich diversity of youth.

Enables students to discern gaps between user/community needs/goals and library services, resources, and facilities; students develop recommendations to close gaps. Covers project management, marketing/communications, and assessment. Course content is contextualized in collaboration with partner libraries.

Basic ideas, concepts and perspectives of management and policy as they apply to the information professions. Students learn to understand and apply these principles to improve organizational effectiveness and promote digital transformation.

Focus on understanding cloud management principles and practices, cloud service models (IaaS, PaaS, SaaS) and deployment strategies (public, private, hybrid), as well as key concepts like scalability, security, and cost optimization. Practical experience in using, creating and managing cloud services.

Introduction to theories, tools, and standards for information organization and access, including cataloging rules and formats, content analysis, indexing, classification, and fundamentals of information retrieval systems.

Public policy and the data, library, and information technology sectors. Access, ethical and responsible artificial intelligence, privacy and security, intellectual property, and freedom of expression. Application of economic, legal, and political science concepts to information policy analysis.

Critical and emerging issues in information innovation. The course presents durable concepts of innovation around a specific innovation in the information field. The innovation is used as context for readings and project.

Introduces the concept of digital transformation and its relationship to information systems within an organization. Uses business case studies to explore topics of digitization, strategic decision making, and organizational culture. Assignments emphasize development of analytical problem solving, presentation, and collaboration skills.

Introduction to field of preservation of cultural heritage, including institutions, contexts and methodologies, concepts of place and culture, objects and resources for study; emphasis also on role of digital applications. Requires research project and presentation.

Basic concepts and technologies of information security, including security properties, vulnerabilities, cryptography, security policies, access control, authentication, firewalls, wireless security, internet security protocols, real life cases, hands on labs, and other related topics. Additional work required of graduate students.

Introduction to preserving library and archival collections, including paper, audio-visual, and digital objects.

A multidisciplinary perspective of risk assessment, modeling, and management. Topics include: concepts of personal accountability versus governance and policy; how organizations define and measure risk and loss; and plan for contingencies.

This course will examine the interrelation of social justice and community engagement in online and naturalistic communities.  Areas of emphasis will explore how gender, race, class and community location (on and off-line) affect and are affected by information. Additional work for graduate students. 

Introduction to the hands-on work of acquiring, processing and preserving archival and manuscript collections. Requires a comprehensive collections project completed at the Special Collections Research Center in Bird Library.

Explore the rapidly evolving landscape of work. Examine how emerging technologies like artificial intelligence, robotics, and extended reality are impacting industries, jobs, and the very nature of work itself. Topics include a history of work, labor organizing, work augmentation, work-life balance, and future worker skills and capabilities. Additional work required for graduate students.

Principles, methods, and techniques of management, development and organization of special collections such as rare books, archives, or pictorial materials, including issues such as bibliographic services and preservation.

Security technologies and management in networked/Internet environments with hands-on skills and research opportunities. This course provides students with the concepts, threats, and key components of network security with technologies and effective management.

Advanced investigation of collection development practices across library types. Includes topics such as, acquisition, maintenance of different types of collections; user and collection analysis; policies and guidelines, budgeting and licensing; evaluation and usage statistics; cooperative collection development; preservation; and ethical issues.

Today's leading issues and challenges in cybersecurity, considering global perspectives that are related to current technology trends. Students will also have research opportunities in the topic area and hands on experiences in information security. Additional work required of graduate students.

Increase the agility of a data science project by improving the process a team uses to execute their project. Explore data science life cycles (e.g., CRISP-DM, TDSP) and collaboration frameworks (e.g., Kanban, Scrum).

Project management as a professional discipline in information and communication technology. Introduction to roles, activities, methods, and tools. Critical review and application of principles. Microsoft Project (Industry standard) will be the tool used in class. Additional work required of graduate students

Human performance characteristics, user/ system communication design alternatives, user behavior research methods, information system organizational impact.

Travel abroad as part of a guided cohort. Course explores how the use of information and digital technologies differ across various cultural, historical, and national contexts. Learn how organizations abroad create and use technology to gain strategic advantage within the competitive global marketplace. Additional work for graduates.

Scripting methods, languages, tools and theory for the efficient and effective management of resources and services in enterprise data systems.

Introduction to scripting techniques for automating, managing, and analyzing data in various formats. The course focuses on practical applications of Python to preprocess, clean, analyze, and visualize data to support data-driven decision-making and the creation of data analysis pipelines.

Concepts and methods of systems analysis through decomposition and modeling. Extensive practice with structured methodologies. Systems analysis and project management techniques. Introduction to automated tools and technologies. Group project to apply skills.

This course is the travel portion of Global Information Technology Abroad. Students enrolled in IDS 350/IDS 650 will register for this course as a requirement to travel when the trip is scheduled.

Definition, development, and management of databases for information systems. Learn data analysis techniques, data modeling, data normalization query writing for information retrieval and query performance tuning using the SQL language.

Prepares students to teach, train, consult, and present programming in information organizations. Focuses on understanding learners and audiences, utilizing educational theory, designing strategies for conveying content, employing inclusive techniques, and assessing effectiveness of instructional episodes.

Linguistic and computational aspect of natural language processing technologies. Lectures, readings, and projects in the computational techniques required to perform all levels of linguistic processing of text.

Introduces concepts and methods for identifying, evaluating, and presenting IT analyses in areas that have potential to cause significant disruption in public and private sector organizations with a focus on social, financial and technological impacts.

Introduction to standards-based methods to support and reinforce library instruction, multiple literacies, reading comprehension in all formats, and information fluency. Development of collaborative instruction and programs that foster student agency and voice, family and cultural literacy.

Philosophies, approaches, and practices of research in information studies, including quantitative, qualitative, critical, historical, and design-based approaches. Create a proposal for an actionable research project, including research ethics, literature review, data collection and analysis, peer review, and communication of results.

Introduction to public libraries within the context of demographic and technological changes and shifting economic and political forces. Topics covered include issues related to social and political environments, user services, diversity, equity, and inclusive services, collections, programming, budgeting, staffing and community outreach.

Survey of academic librarianship, including a variety of public services and technical services domains within the academic library. Emphasizes the role of academic libraries in higher education and attainment of institutional mission.

Understand, analyze, and critique scientific and practical perspectives on what counts as interactivity and intelligence when AI-driven agents interact with humans

Introduces key concepts and techniques in digital curation across humanities, social sciences, and sciences and issues in the technical, service, and social dimensions of curating digital assets.

Enhances the listening, speaking and writing skills of Informaton Studies students with low TOEFL or IELTS scores, or through departmental recommendation. Includes information studies specific writing presentations. Cannot be counted towards degree. By permission only.

Introduces metadata concepts, models, encoding, vocabulary, interoperability, and quality control as well as new development and trends. Students will apply metadata principles, tools, and best practices in creating metadata descriptions and models using established standards.

This course prepares information professionals to develop cultural competencies and provide inclusive services to underrepresented populations. It relates cultural competence to meeting information needs of communities through library and information collection development, outreach, and services.

Contemporary methods of statistical inference for quantitative data, including Bayesian analysis. Students gain practical skills in data preparation, analysis using R, and communicating results for informed, reliable decision-making.

Covers concepts such as data management, transformation, analysis, and machine learning, using R. Hands-on projects and real-world problem-solving help identify when data science is useful, with emphasis on ethical applications. No programming experience required. Additional work for graduate students.

Learn to build Generative AI applications leveraging large language models. Through hands-on projects, students will use libraries and APIs to create conversational agents, Q&A bots, and goal-oriented assistants. Topics covered include prompt engineering, AI conversational memory, output evaluation, and responsible AI practices. Additional work required for graduate students.

Exploration of a problem, or problems, in depth. Individual independent study upon a plan submitted by the student. Admission by consent of supervising instructor(s) and the department.

An introduction to the concepts and techniques needed to build deep learning applications. Gain hands-on experience training neural networks using open-source tools (Python, Tensorflow/Keras). The course culminates in a project applying deep learning methods to real-world challenges.

Through hands-on coding exercises and critical analysis, you¿ll learn to identify and address biases in AI systems, evaluate the social and environmental impact of AI, navigate AI regulations, and apply best practices for responsible AI design and deployment.

Exploration of a topic (to be determined) not covered by the standard curriculum but of interest to faculty and students in a particular semester.

Applications of information security including hands-on experience. Students who successfully complete this course will understand how information security technology is applied to real systems. Additional work required of graduate students.

Provides a comprehensive overview of industry standard machine learning techniques, including an introduction to deep learning. Focus on model building and optimization in Python, real-world applications, and stakeholder communication. Students will apply their skills to an original machine learning project to showcase their skills.

Hands-on enterprise cloud-native software defined network and application/service design, planning and economics; migration/adoption costs, data center resource orchestration. Topics also include cloud elastic sizing, risk management, governance, compliance and data monitoring, and security architecture.

A study of libraries, archives, museums, and national parks as cultural institutions; their missions and operating structures; involvement in joint ventures, both physical and electronic; panelists from and site visits to nearby venues.

Management of academic, public, and special libraries. Relationship between library and its parent institution; internal organization and operation; library information policies; library financing; legislation affecting libraries.

Learn to develop actionable insights from big data using open-source tools (Python and Spark). This course prepares students to build scalable data analytics pipelines and apply advanced machine learning techniques, culminating in a hands-on project tackling real-world challenges.

A broad introduction to data visualization for information professionals. Students will develop a portfolio of resources, demonstrations, recipes, and examples of various data visualization techniques.

Topics related to library leadership offered as available. May include advocacy, budgeting, grant writing, fund-raising, and other topics as appropriate.

Introduction to the concepts of data warehousing and business intelligence (BI). Data warehouse architectures and design. Dimensional modeling, extract-load-transform (ELT) in the SQL language. Emphasis on using data warehouses to make better organizational decisions.

Introduces concepts and practices, using an organization-wide enterprise architecture as context. The purpose of an IT security architecture is to ensure proper levels of information confidentiality, integrity, and availability are provided for an organization's information and data.

Understand and develop information security technology, law and policy risks and vulnerability analysis skills for management and operations of business and government. Technology, law, regulation, and policy for information security best practices and compliance.

This course provides a conceptual and applied introduction to Large Language Models (LLMs), emphasizing informed use, evaluation, and responsible deployment. Students will learn how LLMs process and generate texts, evaluate their capabilities and limitations, and design applications for information-rich environments.

Analytic dashboards find valuable insights from large scale data. Students will gain knowledge of human visual reasoning, and obtain technical skills necessary to design, develop and implement analytic dashboards for business, government, or personal data.

Seminar. Integration of previous learning on the various components of management, user needs, and technologies. In-depth review and use of case studies on a range of critical information resources management areas.

Analyze relational and non-relational databases and corresponding database management system architectures. Learn to build complex database objects to support a variety of needs from big data and traditional perspectives. Data systems performance, scalability, security. Additional work required for graduate students.

Creation of an online reflective portfolio that demonstrates successful achievement of all program learning outcomes for the MSLIS degree.

Hands-on experience with qualitative and quantitative research methods in Information Science. Covers the entire research process¿from question development to data analysis¿while emphasizing ethical considerations and diverse research techniques like surveys, interviews, and experiments.

Classical statistical procedures used in information transfer research. Emphasis on underlying rationale for each procedure and on criteria for selecting procedures in a given research situation.

Reflect on and curate a portfolio of AI or data science projects completed during the program. Through an ePortfolio and reflection document, demonstrate how your work has aligned with your program learning outcomes. The portfolio serves as a professional showcase for future career opportunities. No new projects are required.

Introduces students to a broad range of information-focused theories. Through critical reading, writing, and discussion, students will critically engage course concepts and apply them to their own research interests.

Selected areas within the information field, emphasizing related disciplines and their relationships to the diagnosis of information needs and the collection, storage, management, regulation and dissemination of information.

This course defines what it means to be a scientist (Ph.D.) or practitioner/researcher (DPS), what is meant by science, and what are some of the core concepts in the broad intellectual spaces represented by faculty at this (and other) iSchool(s). As such, this overview is very directed towards concepts, perspectives, and issues that are relevant to the doing of science by researchers in iSchools.

Practical, mentor-led experience in the research process, including planning, design, data collection, analysis, writing, and/or funding. Experiences are complemented by workshops and discussions.

Theory and practice in the analysis, design, management, and evaluation of existing and hypothetical information systems, including computerized storage and retrieval systems, libraries, management systems, and networks.

Practical, mentor-led experience in teaching, including work in course design, pedagogical strategies, lecture and activity delivery, grading, classroom management, and/or accessibility. Experiences are complemented by workshops and discussions.

Residential seminar for Doctorate of Professional Studies distance students. Skill building and mentoring for doctoral coursework and dissertation preparation. Portfolio evaluation of work accumulated during the semester.

Participation in a supervised and evaluated field experience. Requires contract approved by advisor, faculty supervisor, and field agency before registration.

Fully supervised internship experience for graduate students in the MSIS degree program. Must meet GPA requirements and complete a learning agreement with site supervisor.

Fully supervised and evaluated school-based library experience at the elementary and secondary levels. Includes online seminar. Must meet GPA/program requirements and complete a learning agreement with site supervisor.

Fully supervised internship experience. Must meet GPA requirements and complete a learning agreement with site supervisor.

Fully supervised internship experience. Must meet GPA requirements and complete a learning agreement with site supervisor. Pre-req: IST ADS master's students only.

Exploration of a problem, or problems, in depth. Individual independent study upon a plan submitted by the student. Admission by consent of supervising instructor(s) and the department.