BSIS Curriculum, Emphasis Areas & Courses

Faculty lecturing

The iSchool's on-campus, STEM-designated Bachelor of Science in Information Science (BSIS) equips students with the versatile, cross-disciplinary skills they need to solve society’s most critical information challenges.

120

Units to Complete Degree, Includes:
42 Upper-Division
47 Major Coursework
18 Minor or Dual Degree

2

Emphasis Areas:
Data Science
Interactive & Immersive Technologies

Learning Outcomes

Regardless of the emphasis area students choose, learning outcomes in the BSIS are the same, and are designed to provide the hands-on computational, mathematical and technological foundation to analyze and extend the digital world, opening the door to a wide variety of engaging careers.

  • Students will establish the ability to exercise the four key techniques of computational thinking (decomposition, pattern recognition, abstraction and algorithms) in solving information and data challenges.
  • Students will acquire the skills of collecting, manipulating and analyzing different types of data at different scales, and interpreting the results properly.
  • Students will demonstrate understanding of the use of information and communication technologies and the implications of such use in, for example, scientific and social uses of information and social, cultural and economic implications of digital life and culture.
  • Students will demonstrate the ability to conduct a research project using appropriate and ethical methods, including proper citation of sources.
  • Students will demonstrate facility using basic research methods; for example, research design; statistics and analysis; organization, identification and location of data and information including open- and closed-access sources; and presentation of findings in oral, written and multimedia form, including proper use of and citation of sources.
  • Students will be able to recognize and analyze ethical and policy concerns raised by new technologies and will be able to apply ethical thinking to real-world cases and craft effective solutions.
  • Students will acquire the skills, knowledge and self-understanding to communicate with and effectively work and interact across cultures and with diverse people and groups.
  • Students will be able to identify and apply professional ethics and standards relevant to their career and aspirations.
  • Students will demonstrate knowledge of career possibilities and further education options and opportunities open to them relative to their plan of study and will set goals and make plans beyond their expected graduation.

Sample Four-Year Plan

120 units are required for graduation. A minor with a minimum of 18 units, or a double major, is required.

In addition to the required foundation, general education and minor or double major courses, plus five core courses taken in the first two years, BSIS students select one of two emphasis areas—Interactive and Immersive Technologies, or Data Science—requiring 15 units. BSIS students must also meet the following additional requirements to complete the degree: 3 units from Computational Arts and Media; 3 units from Society; a Research Methods course (ESOC 302); 3 units of Engagement: either independent study, directed research, an internship or ESOC 480: Digital Engagement; and the 3-unit Senior Capstone (ISTA 498).

Click to view sample courses by year:

Year 1 | Fall

ENGL 101: First-Year Composition 3 units
MATH (based on placement) 3 units
UNIV 101: Introduction to the General Education Experience 1 unit
General Education: Exploring Perspectives 3 units
First-Semester Language 4 units
TOTAL 14 units

Year 1 | Spring

ENGL 102: First-Year Composition 3 units
ISTA 100: Great Ideas of the Information Age 3 units
General Education: Exploring Perspectives 3 units
General Education: Building Connections 3 units
Second-Semester Language 4 units
TOTAL 16 units

Year 2 | Fall

ISTA 116: Statistical Foundations of the Information Age 3 units
ISTA 130: Computational Thinking and Doing 4 units
ISTA 161: Ethics in a Digital World 3 units
General Education: Exploring Perspectives 3 units
General Education: Exploring Perspectives 3 units
TOTAL 16 units

Year 2 | Spring

ISTA 131: Dealing with Data 4 units
Computational Arts & Media Course 3 units
General Education: Building Connections 3 units
Minor Course 3 units
Minor Course 3 units
TOTAL 16 units

Year 3 | Fall

UNIV 301: General Education Portfolio 1 unit
ESOC 302: Quantitative Methods for the Digital Marketplace 3 units
General Education: Building Connections 3 units
Major Emphasis Course 3 units
Minor Course 3 units
Minor Course 3 units
TOTAL 16 units

Year 3 | Spring

Societies Course 3 units
Major Emphasis Course 3 units
Major Emphasis Course 3 units
Minor Course 3 units
Minor Course 3 units
TOTAL 15 units

Year 4 | Fall

Major Engagement Course* 3 units
Major Emphasis Course 3 units
Upper-Division Elective 3 units
Upper-Division Elective 3 units
Additional Elective Course 3 units
TOTAL 15 units

Year 4 | Spring

ISTA 498: Senior Capstone 3 units
Major Emphasis Course 3 units
Additional Elective Course 3 units
Additional Elective Course 3 units
TOTAL 12 units
TOTAL DEGREE CREDITS 120 units

* Engagement course, such as an internship, may be completed over the summer.

This is a sample plan and is subject to change based on catalog year, placement tests, AP/CLEP credit, transfer work, minor requirements, summer school, etc. The official degree requirements may be found in the University General Catalog and all University of Arizona students should refer to the Academic Advising Report for specific graduation requirements.

Curriculum, Emphasis Areas & Courses

Bachelor's in Information Science students take a mix of Foundations, General Education, Core Major, Emphasis Area, Computational Arts & Media, Society, Research Methods, Engagement, Minor and Electives courses, subject to change based on catalog year, placement tests, AP/CLEP credit, transfer work, minor requirements, summer school, etc.

Choose from either the Data Science or Interactive and Immersive Technologies emphasis area.

Click a link below to learn more and view course information:

Foundations

Specific unit requirements may vary based on placement and/or prior college-level coursework:

  • First-year English or equivalent
  • MATH 122B or MATH 113 or MATH 116
  • Second-semester second language proficiency

General Education

  • Introduction to General Education (1 unit)
  • Exploring Perspectives Courses (12 units, including at least one course from each domain: Artist, Humanist, Natural Scientist, Social Scientist)
  • Building Connections Courses (9 units)
  • General Education Capstone (1 unit)

Learn More About UArizona General Education Requirements

Students who started before Spring 2022 will follow the previous UArizona GenEd requirements:

  • Tier 1 Individuals & Societies (6 units)
  • Tier 1 Traditions & Cultures (6 units)
  • Tier 1 Natural Sciences (6 units)
  • Tier 2 Humanities (3 units)
  • Tier 2 Individuals & Society (3 units)
  • Tier 2 Arts (3 units)
  • Diversity (3 units)

Important ideas and applications of information science and technology in the sciences, humanities and arts. Information, entropy, coding; grammar and parsing; syntax and semantics; networks and relational representations; decision theory, game theory; and other great ideas form the intellectual motifs of the Information Age and are explored through applications such as robotic soccer, chess-playing programs, web search, population genetics among others.

Understanding uncertainty and variation in modern data: data summarization and description, rules of counting and basic probability, data visualization, graphical data summaries, working with large data sets, prediction of stochastic outputs from quantitative inputs.  Operations with statistical computer packages such as R.

An introduction to computational techniques and using a modern programming language to solve current problems drawn from science, technology, and the arts. Topics include control structures, elementary data structures, and effective program design and implementation techniques. Weekly laboratory.

**Programming-intensive Course, College Algebra recommended

At the core of Information Science lies the digital data that is the object of study. This course aims to introduce the tools, techniques, and issues involved with the handling of this data: where it comes from, how to store and retrieve it, how to extract knowledge from the data via analysis, and the social, ethical, and legal issues involved in its use. Throughout the course, students will be given hands-on experience with actual datasets from a variety of sources including social media and citizen science projects, as well as experience with common tools for analysis and visualization. Students will also examine topical case studies involving legal and ethical issues surrounding data.

This course explores the social, legal, and cultural fallout from the exponential explosion in communication, storage, and increasing uses of data and data production. In this class, we emphasize the opposing potentials of information technologies to make knowledge widely available and to distort and restrict our perceptions. In a world of rapid technological change, topics include (but are not limited to): eavesdropping and secret communications, privacy; Internet censorship and filtering, cyberwarfare, computer ethics and ethical behavior, copyright protection and peer-to-peer networks, broadcast and telecommunications regulation, including net neutrality, data leakage, and the power and control of search engines.

 
CSC 110 may substitute for ISTA 130.

For students who select the Data Science emphasis area, choose from:

This course will guide students through advanced applications of computational methods for social science research. Students will be encouraged to consider social problems from across sectors, like health science, education, environmental policy and business. Particular attention will be given to the collection and use of data to study social networks, online communities, electronic commerce and digital marketing. Students will consider the many research designs used in contemporary social research and will learn to think critically about claims of causality, mechanisms, and generalization in big data studies.

 

An introduction to the mathematical theories of probability and information as tools for inference, decision-making, and efficient communication. Topics include discrete and continuous random variables, measures of information and uncertainty, discrete time/discrete state Markov chains, elements of Bayesian inference and decision-making, Bayesian and Maximum Likelihood parameter estimation, and elementary coding theory.

This course will introduce students to the fundamental concepts and tools used to convey the information contained within large, complex data sets through a variety of visualization techniques. Students will learn the fundamentals of data exploration data via visualizations, how to manipulate and reshape data to make it suitable for visualization, and how to prepare everything from simple single-variable visualizations to large multi-tiered and interactive visualizations. Visualization theory will be presented alongside the technical aspect of the course to develop a holistic understanding of the topic.

This course introduces students to the theory and practice of data mining for knowledge discovery. This includes methods developed in the fields of statistics, large-scale data analytics, machine learning, and artificial intelligence for automatic or semi-automatic analysis of large quantities of data to extract previously unknown and interesting patterns. Topics include understanding varieties of data, classification, association rule analysis, cluster analysis, and anomaly detection. We will use software packages for data mining, explaining the underlying algorithms and their use and limitations. The course will include laboratory exercises, with data mining case studies using data from biological sequences and networks, social networks, linguistics, ecology, geo-spatial applications, marketing and psychology.

This course will be inviting for a wide variety of students from across disciplines, and they will learn how to use industry standard tools and practices to make large data sets usable for scientists and other decision makers. From data collection and preparation, to the creation of big data stores, databases, or systems to make data flow, this course will focus on the practical work needed to prepare big data for analyses across contexts. Students will be introduced to a variety of technical tools for data management, storage, use, and manipulation.

This course surveys the techniques central to the modern practice of extracting useful patterns and models from large bodies of data and the theory behind these techniques.  Students will learn the purpose, power, and limitations of models, with concrete examples from business and science.  Course subject matter may include classification and regression, supervised segmentation and decision trees, similarity/distance metrics and recommender systems, clustering and nearest neighbors, support vector machines, understanding and avoiding overfitting, natural language processing and sentiment analysis, machine learning, neural networks, and AI, and logistic regression.

This course will provide an introduction to informatics application programming using the python programming language and applying statistical concepts from a first semester statistics course. A key goal of this course is to prepare students for upper division ISTA courses by expanding on the skills gained in ISTA 116 and 130 but will be broadly applicable to any informatics discipline.  Throughout the semester students will be faced with information application problems drawn from several different disciplines in order to expand their breadth of experience while simultaneously increasing their depth of knowledge of scientific and informatics programming methods.  Students will practice problem decomposition and abstraction, gaining experience in identifying commonly occurring information processing issues and in applying well-known solutions.  In addition, students will design their own algorithmic solutions to problems and will learn how to effectively compare different solutions, evaluating efficiency in order to choose the best solution for a given problem. Periodic code reviews will be held in order to expose students to a range of different solution methods, which will aid them in discovering weaknesses in their own work and will improve their ability to communicate with others on technical topics.  The course will include an introduction to the python scientific computing libraries and other statistical packages.  Additional course topics will include the use of version control systems, software profiling, general software engineering practices and basic shell scripting.

Natural language processing (NLP) is the study of how we can teach computers to use language by extracting knowledge from text, and then use that knowledge in some meaningful way.  In this introductory course, we will examine the fundamental components on which natural language processing systems are built, including frequency distributions, part of speech tagging, syntactic parsing, semantics and analyzing meaning, search, introductory information and relation extraction, and structured knowledge resources.  We will also examine pragmatic concerns in processing raw text from real-world sources.

Bayesian modeling and inference is a powerful modern approach to representing the statistics of the world, reasoning about the world in the face of uncertainty, and learning about it from data. It cleanly separates the notions of representation, reasoning, and learning. It provides a principled framework for combining multiple source of information such as prior knowledge about the world with evidence about a particular case in observed data. This course will provide a solid introduction to the methodology and associated techniques, and show how they are applied in diverse domains ranging from computer vision to molecular biology to astronomy.

Machine learning describes algorithms which can modify their internal parameters (i.e., "learn") to recognize patterns and make decisions based on examples or through interaction with the environment.  This course will introduce the fundamentals of machine learning, will describe how to implement several practical methods for pattern recognition, feature selection, clustering, and decision making for reward maximization, and will provide a foundation for the development of new machine learning algorithms.

Students will learn from experts from projects that have developed widely adopted foundational Cyberinfrastrcutrue resources, followed by hands-on laboratory exercises focused around those resources. Students will use these resources and gain practical experience from laboratory exercises for a final project using a data set and meeting requirements provided by domain scientists. Students will be provided access to computer resources at: UA campus clusters, iPlant Collaborative and at NSF XSEDE. Students will also learn to write a proposal for obtaining future allocation to large scale national resources through XSEDE.

Data Warehousing and Analytics In the Cloud will utilize concepts, frameworks, and best practices for
designing a cloud-based data warehousing solution and explore how to use analytical tools to perform
analysis on your data. In the first half of the course, I will provide an overview of the field of Cloud
Computing, its main concepts, and students will get hands-on experience through projects which utilize
cloud computing platforms. In the second half of the course, we will examine the construction of a cloudbased
data warehouse system and explore how the Cloud opens up data analytics to huge volumes of
data.
 

This course introduces the key concepts underlying statistical natural language processing. Students will learn a variety of techniques for the computational modeling of natural language, including: n-gram models, smoothing, Hidden Markov models, Bayesian Inference, Expectation Maximization, Viterbi, Inside-Outside Algorithm for Probabilistic Context-Free Grammars, and higher-order language models.  Graduate-level requirements include assignments of greater scope than undergraduate assignments. In addition to being more in-depth, graduate assignments are typically longer and additional readings are required.This course introduces the key concepts underlying statistical natural language processing. Students will learn a variety of techniques for the computational modeling of natural language, including: n-gram models, smoothing, Hidden Markov models, Bayesian Inference, Expectation Maximization, Viterbi, Inside-Outside Algorithm for Probabilistic Context-Free Grammars, and higher-order language models.  

The methods and tools of Artificial Intelligence used to provide systems with the ability to autonomously problem solve and reason with uncertain information. Topics include: problem solving (search spaces, uninformed and informed search, games, constraint satisfaction), principles of knowledge representation and reasoning (propositional and first-order logic, logical inference, planning), and representing and reasoning with uncertainty (Bayesian networks, probabilistic inference, decision theory).

Most of web data today consists of unstructured text. This course will cover the fundamental knowledge necessary to organize such texts, search them a meaningful way, and extract relevant information from them. This course will teach natural language processing through the design and development of end-to-end natural language understanding applications, including sentiment analysis (e.g., is this review positive or negative?), information extraction (e.g., extracting named entities and their relations from text), and question answering (retrieving exact answers to natural language questions such as “What is the capital of France” from large document collections). We will use several natural language processing toolkits, such as NLTK and Stanford’s CoreNLP. The main programming language used in the course will be Python, but code written in Java or Scala will be accepted as well.

Most of the web data today consists of unstructured text. Of course, the fact that this data exists is irrelevant, unless it is made available such that users can quickly find information that is relevant for their needs. This course will cover the fundamental knowledge necessary to build such systems, such as web crawling, index construction and compression, boolean, vector-based, and probabilistic retrieval models, text classification and clustering, link analysis algorithms such as PageRank, and computational advertising. The students will also complete one programming project, in which they will construct one complex application that combines multiple algorithms into a system that solves real-world problems.

Neural networks are a branch of machine learning that combines a large number of simple computational units to allow computers to learn from and generalize over complex patterns in data. Students in this course will learn how to train and optimize feed forward, convolutional, and recurrent neural networks for tasks such as text classification, image recognition, and game playing.

This course covers theory, methods, and techniques widely used to design and develop a relational database system and students will develop a broad understanding of modern database management systems. Applications of fundamental database principles in a stand-alone database environment using MS Access and Windows are emphasized. Applications in an Internet environment will be discussed using MySQL in the Linux platform.

For students who select the Interactive and Immersive Technologies emphasis area, choose from:

Algorithms are a crucial component of game development. This course will provide students with an in-depth introduction to algorithm concepts for game development. The course will cover basic algorithm and data structures concepts, basic math concepts related to game algorithms, physics and artificial intelligence based game algorithms that are supplemented with modern examples. Unity Game Engine along with C# programming language will be used throughout the class.

This course provides a comprehensive survey of video game production practices. Students work on game development assignments for presentation in a professional portfolio. The course topics include: collaborative technologies, software design patterns for games, spatial transformations, and technical considerations surrounding game art, such as authoring sprites, 3D models, animations, texture mapping, and writing shaders. Students will be given periodic assignments that reinforce lessons from class.

This course provides an introduction to software and hardware packages that allow students to explore rapid prototyping, object design, and physical computing using Computer-Aided Design (CAD) software, 3D printing technology, laser cutting, and Arduino microcontrollers. The processing language will also be introduced, and used for visualization and interfacing. This interdisciplinary course combines elements of computer science, electrical engineering, mechanical design, robotics, and visualization.

This is a hands-on practical course where fluency is largely built through experience building projects, rather than written exams. This course will require extensive technology training and substantial reference to open resources on the web. This course includes a team-based design competition as a final project.

This course will introduce students to the fundamental concepts and tools used to convey the information contained within large, complex data sets through a variety of visualization techniques. Students will learn the fundamentals of data exploration data via visualizations, how to manipulate and reshape data to make it suitable for visualization, and how to prepare everything from simple single-variable visualizations to large multi-tiered and interactive visualizations. Visualization theory will be presented alongside the technical aspect of the course to develop a holistic understanding of the topic.

Introduction to event-driven programming and prototype-oriented programming using JavaScript. Course topics include JavaScript language basics, Document Object Model (DOM) interaction and manipulation, DOM event management, and dynamic media creation.

This course will provide an introduction to informatics application programming using the python programming language and applying statistical concepts from a first semester statistics course. A key goal of this course is to prepare students for upper division ISTA courses by expanding on the skills gained in ISTA 116 and 130 but will be broadly applicable to any informatics discipline.  Throughout the semester students will be faced with information application problems drawn from several different disciplines in order to expand their breadth of experience while simultaneously increasing their depth of knowledge of scientific and informatics programming methods.  Students will practice problem decomposition and abstraction, gaining experience in identifying commonly occurring information processing issues and in applying well-known solutions.  In addition, students will design their own algorithmic solutions to problems and will learn how to effectively compare different solutions, evaluating efficiency in order to choose the best solution for a given problem. Periodic code reviews will be held in order to expose students to a range of different solution methods, which will aid them in discovering weaknesses in their own work and will improve their ability to communicate with others on technical topics.  The course will include an introduction to the python scientific computing libraries and other statistical packages.  Additional course topics will include the use of version control systems, software profiling, general software engineering practices and basic shell scripting.

This course continues the exploration of creative coding that began in ISTA 303. Students will develop experimental and creative works based, in part, on techniques from the fields of human-computer interaction, computer vision, virtual reality, machine learning, and other disciplines that have the potential to impact our culture through the introduction of new technologies. Aside from gaining technical proficiencies needed to engage with these topics (e.g., software engineering, physical computing techniques, familiarity with multimedia packages and libraries), students will have the opportunity to explore the use of novel interaction devices (e.g., Kinect, Wii, LeapMotion, Glasses, and Oculus Rift) as well as to experiment with a range of digital media environments (e.g., projection mapping, live coding, sonification, mobile devices, physical sensors,augmented reality, immersive systems). Moreover, students will become more familiar with the history and current state of the fields of new media art and creative coding. Students will read widely from journal articles and from media arts conference and festival proceedings, and will be expected to document their own work in a clear, professional manner, both through writing assignments and the creation of an online portfolio of creative projects. By the end of this course students will have the ability to participate meaningfully (through the implementation and documentation of creative projects) in contemporary discourse regarding art and technology.

The field of Human Computer Interaction (HCI) encompasses the design, implementation, and evaluation of interactive computing systems. This course will provide a survey of HCI theory and practice. The course will address the presentation of information and the design of interaction from a human-centered perspective, looking at relevant perceptive, cognitive, and social factors influencing in the design process. It will motivate practical design guidelines for information presentation through Gestalt theory and studies of consistency, memory, and interpretation. Technological concerns will be examined that include interaction styles, devices, constraints, affordances, and metaphors. Theories, principles and design guidelines will be surveyed for both classical and emerging interaction paradigms, with case studies from practical application scenarios. As a central theme, the course will promote the processes of usability engineering, introducing the concepts of participatory design, requirements analysis, rapid prototyping, iterative development, and user evaluation. Both quantitative and qualitative evaluation strategies will be discussed.

Virtual reality (VR) is an emerging technology that has recently been widely used in various areas, such as education, training, well-being, and entertainment. VR offers a highly immersive experience as the head mounted displays surround a 360-degree view of the user. It encompasses many disciplines, such as computer science, human computer interaction, game design and development, information science, and psychology. This course merges a theoretical and practical approach to give students the necessary knowledge that is required to design, develop, and critique virtual reality games and applications.

Designed to provide students with a foundational understanding of the evolution of the internet as a digital medium, the course will examine the early- stages of ISPs as information gateways through Portals to Search as a unifying experience layer.  Additionally, the course will examine the current influences of social media, Generative AI as well as analyze the ever-changing business of sports media. Throughout, we will discuss the implications of digital media on marketing and advertising practices, both the benefits and the downsides of the digital world. By examining the inner workings of some of the most interesting and fastest-growing companies in the digital world (e.g. AppleTV, Google, Facebook, Snap, Twitter, and TikTok), students will receive a first-hand account of how digital marketing and media are evolving from execs from these companies and hear where career opportunities may be trending.

Students may only apply a course to either their emphasis area or the Computational Arts and Media requirement, but not both.

Choose one class from:

This course explores the process of creating interactive computer art by teaching the essential principles of programming.

This course introduces fundamental theories, principles and practices of 3D digital modeling, rendering, and rapid prototyping. Students are given a thorough overview of 3D modeling techniques including: production of geometric and organic surfaces and forms using both NURBs and polygon construction, texturing, and lighting. Minimal materials fee for rapid prototyping assignment.

This course will lay a foundation for understanding how stories shape communities, identities, memories, and perspectives on our lives. In addition, this course will provide opportunities for the theoretical analysis of self representation, composite narratives on behalf of others, cultural heritage, and memories as they are preserved and performed within stories and through narrative. Influences on digital storytelling such as the sociocultural context, the institutional contexts of production the audience, and the needs or goals of the digital storyteller will be examined. Students will be required to call on their own intellectual, emotional, and imaginative processes, as well as to develop their own skills in digital storytelling, interviewing, oral history collection, and the use of relevant digital storytelling tools.

We are living in a time when nearly everyone has the means to make movies, music and photos using just their own personal tools like smartphones, iPads, and similar mobile gadgets. This course will develop and refine skills and understanding of multimedia in contemporary culture. Offering a survey of innovative works in film and information arts, this course will allow students a hands-on opportunity to respond to concepts covered in class using self-produced media. This course will address how information functions in time-based forms of multimedia and video in this era of interactive information and displays. Drawing on historical precedents in the media and computational arts, this course focuses on both linear and non-linear approaches of using image, sound and text to create critical and creative works that function in a the context of social media and our contemporary digital society. How and why do certain images, music or films affect us so profoundly? We will address this question through a study of the components of media literacy that include: Production, Language, Representation, and Audience. These concepts will be examined through a cross-section of writers including: Marshall McLuhan, John Berger and Susan Sontag.

This course examines the ways in which computing and information science support and facilitate the production and creation of art in current society. A particular focus of the course will be to discuss how artists have used advances in technology and computing capacity to explore new ways of making art, and to investigate the relationships between technical innovation and the artistic process. This class satisfies a Tier II: Arts General Education Requirement. Alternatively, this class can be applied towards the ISTA BA/BS and ISTA minor. Tier II Gen-eds can be double-dipped with a minor but not a major. 

This course will provide the student with the information and experience necessary for the creation and manipulation of digital audio. Students will have the opportunity to experience the music-making process with the technology tools and techniques that are common in both home and professional studios. The class will make use of a variety of software packages designed for contemporary music production, explaining the universal techniques and concepts that run through all major software programs. Topics will include musical analysis, MIDI control, synthesis techniques, audio editing, and audio mixing. Lab assignments will emphasize hands-on experience working with musical hardware and software to provide the necessary skills to create music based on today's musical styles. The course provides the foundation for further study, creative applications, and personal expression.

This course provides an introduction to software and hardware packages that allow students to explore rapid prototyping, object design, and physical computing using Computer-Aided Design (CAD) software, 3D printing technology, laser cutting, and Arduino microcontrollers. The processing language will also be introduced, and used for visualization and interfacing. This interdisciplinary course combines elements of computer science, electrical engineering, mechanical design, robotics, and visualization.

This is a hands-on practical course where fluency is largely built through experience building projects, rather than written exams. This course will require extensive technology training and substantial reference to open resources on the web. This course includes a team-based design competition as a final project.

An introduction to web design and development, with an emphasis on client-side technologies. Topics include HTML, Cascading Style Sheets (CSS), JavaScript, and web design best practices.

A significant portion of the human brain is devoted to understanding spatial data and its relation to the world. Through the ages humans have naturally developed external representations of such information for communication, planning, understanding, and entertainment. Further, the digital age has led to an explosion of images available to everyone in forms that are convenient to share, manipulate, and automatically mine for information. In this thematic course we will study images from perspectives that transcend disciplines, and applicable to many of them, including the arts, science and biomedicine, computational intelligence, geography, and security. We will study what images are, how images are stored and distributed, the reproduction of images, how they can be manipulated, using images for visualization, and extracting semantics from images.

This course is a hands-on, project-based approach to understanding and designing art installations. Enrollees will learn principles, tools, and techniques of rapid prototyping and installation design, and will collaborate to design and implement a large-scale installation by the end of the semester. The course lectures will also provide an overview of the history, theory, and aesthetics of installation art.

This course continues the exploration of creative coding that began in ISTA 303. Students will develop experimental and creative works based, in part, on techniques from the fields of human-computer interaction, computer vision, virtual reality, machine learning, and other disciplines that have the potential to impact our culture through the introduction of new technologies. Aside from gaining technical proficiencies needed to engage with these topics (e.g., software engineering, physical computing techniques, familiarity with multimedia packages and libraries), students will have the opportunity to explore the use of novel interaction devices (e.g., Kinect, Wii, LeapMotion, Glasses, and Oculus Rift) as well as to experiment with a range of digital media environments (e.g., projection mapping, live coding, sonification, mobile devices, physical sensors,augmented reality, immersive systems). Moreover, students will become more familiar with the history and current state of the fields of new media art and creative coding. Students will read widely from journal articles and from media arts conference and festival proceedings, and will be expected to document their own work in a clear, professional manner, both through writing assignments and the creation of an online portfolio of creative projects. By the end of this course students will have the ability to participate meaningfully (through the implementation and documentation of creative projects) in contemporary discourse regarding art and technology.

Choose one class from:

The focus of this course is on how social information is produced though language and identity work online, focusing on patterns of talk and interactional rules and practices across contexts (e.g., text-messaging, online communities, personal identity work, and transnational blogs). As part of this focused study of talk, this course will explore how online language use can create, maintain, reproduce, or disrupt roles and related norms (e.g., those of a friend, student, expert, or political agent), as well as identities and social categories (e.g., gender, sexuality, race, disability, or nationality). This course will also focus on the broader discourses on a 'global' level, examining human collaboration online for practices tied to elitism, the movement of social capital, racism, power, and the cultural production of inequalities.

This course will lay a foundation for theoretical analyses of how people socially create and negotiate information socially, digitally, virtually, and through AI. In addition, this course investigates a variety of approaches ranging from critical cultural studies to behavioral research, considering the differing ways to think about social life and information in contemporary times. Lastly, this class will survey the theoretical underpinnings of new media research across a variety of topic areas to include gaming, eSports, eCommerce, digital gig labor, online communities, and networked publics.

In the early 21st Century, we see publishing in the throes of dramatic changes, from print to electronic most obviously but also in who authors books, the economics of publishing, and how books get to readers. These changes remind us that the dynamics of the movement of the written word to its audience are an integral part of the society in which books are written, produced, and circulate. This 3-credit course takes an historical perspective on publishing, which we will define as the processes by which books come into being in multiple copies and are distributed to reach their audiences. We will start with ancient societies all over the world, and we will investigate the circumstances across societies in which books distinguish themselves from administrative records and begin to serve the needs of the literate elite.  We will examine the way the physical form of the book and the technologies for producing it arise from the circumstances of each society, and in turn, how that physical format conditions the character of books and their use. We will trace the rise of publishing practices and identify the factors necessary for the reproduction and distribution of books to form an actual trade in books in varying societies. As we work our way from the ancient world to the early modern world, we will compare publishing practices in different societies and explore commonalities and differences in the relationships that develop between the creation, reproduction and distribution of books.  Of particular focus will be our comparison of the rise of publishing and book trades in Europe, Asia, and the Arab world before 1450. After the introduction of printing with metal moveable type in Europe, associated with Gutenberg in approximately 1450, we will have an opportunity to observe the changes that this new technology makes in publishing and the book trade, by comparing the mature manuscript book trade of the late middle ages (Middle Ages) to that of the hand-press book publishing of…

This course will look at how commerce in information content (websites, books, databases, music, movies, software, etc.) functions. We will discuss things like switching costs, net neutrality, the long tail, differential pricing, and complementary goods. We will address the following sorts of questions:

- Why do so many information producers give away content (such as "apps" for mobile phones) for free? How do companies (such as Google and Facebook) stay in business when no one has to pay to use their services?
- What are contemporary practices with regard to (Regarding) purchasing access to information content? For instance, why do we tend to buy books, but only rent movies? Also, how do new modes of content provision (such as Pandora and Spotify) change the way that creators get paid for their work?
- Why are there restrictions on how information content can be used? For instance, why can you play the DVD that you bought on your trip to Europe on the DVD player that you bought at home in the United States?

But why should anybody other than an economist care about the answers to these sorts of questions?

The world now runs on the production, dissemination, and consumption of information. All of us constantly access all sorts of information, through all sorts of devices, from all sorts of providers. We read and interact with websites, we query databases, and we communicate with each other via social media. These sorts of activities permeate both our personal and professional lives. In order to (To) successfully navigate this digital world, information consumers, information producers, and information policy makers need to understand what sorts of information goods are likely to be available and how much they are likely to cost.

We cannot learn enough about digital commerce simply by studying the various information technologies that are now available to create…

This course provides a powerful introduction to some of the criminal activities taking place in relation to digital information, big data, and social media. Related to the exploration of criminal activity in an eSociety, this course focuses on some of the most common legal issues faced today, with regard to our own personal data (e.g., our health histories, our genetic makeup, our cloud-based photos and messages, our past) and in relation to organizational or political data on social media and in society. In this course, students as future technologists, will be exposed to the 'dark side' of this current 'information society' (e.g., deception, cybercrime) as well topics such as big data privacy, digital disruptions, consumer data and related sales, gaming protections, youth safety online, big science data sharing issues and related trust, digital security, as well as how certain groups -- law firms, advocacy groups, marketing professionals, and political or lobbying groups -- are mining data for particular use. Students will be required to consider recent court cases and contentions around the use, management, and protection of data in society as well as the risk humans face in this digital information and mediated age

This course introduces key concepts and skills needed for those working with information and communication technologies (ICT). Students will be exposed to hardware and software technologies, and they will explore a wide variety of topics including processing and memory systems, diagnostics and repair strategies, operating systems in both desktop and mobile devices. As part of this course, students will consider current technological disruptions, those issues emerging as technologies and social needs collide. Students we also learn about design issues and user needs tied to mobile or computer applications and web-based tools, sites, games, data platforms, or learning environments.

This course is a broad survey of the processes, theories, and practices around instructional technologies that can be applied to various learning situations.  Students will study and apply research and theory on technology adoption, analysis, and support, along with instructional design, learning theories, and training needs analysis.  The course will also guide students through the design of effective tech-supported training, technology selection dependent upon learning situations, evaluation of chosen learning technologies, and considerations in instructional technology piloting, adoption, and support.  By the end of this course, students will make educated decisions about technology implementation across diverse learning environments.

This course focuses on the ethical issues that arise in the context of new and emerging information technologies-- e.g., threats to privacy of ubiquitous technological surveillance, limitations on access created by digital rights management. The course will use the framework of ethical theory to analyze these issues and to propose policy solutions. The goal of the course is to give students the necessary theoretical foundation to be involved in the evaluation and construction of information policies at the local, national, and international level. The course will focus on three core areas where digital dilemmas arise--information access, information privacy, and intellectual property. In order to achieve depth as well as breadth, the course will put one of these issues at the center and discuss the others in relation to it. So, for instance, the course may focus on Intellectual Property looking at the threats and benefits of IP to privacy and access. This syllabus provides an overview of the range of topics that may be discussed.

Security is about protecting assets, such as money and physical possessions.  For instance, we use walls, locks, burglar alarms, and even armed guards to keep other people from stealing and/or destroying our stuff. These days, information is typically one of our most important assets.  Thus, we have to worry about the possibility of other people stealing and/or destroying it. For instance, criminals threaten our data with scareware or ransomware in order to extort money from us. 

In today's digital society, people have access to a wide variety of information sources and scientific data. In this course, students will learn about the role of science and scientific data in society, and they will consider means for making science information findable and understandable for a wide variety of audiences. This course will provide students an interdisciplinary experience for considering science data and how that information gets shared across contexts.

Special topics courses are offered to allow students to explore specialized topics not covered in the program curriculum. Multiple topics might be offered in any given year, and specialized topic descriptions will be advertised by the School for students interested in enrolling in the course.

Special topics courses are offered to allow students to explore specialized topics not covered in the program curriculum. Multiple topics might be offered in any given year, and specialized topic descriptions will be advertised by the School for students interested in enrolling in the course.

This course will explore broad research paradigms and theoretical approaches that inform contemporary social research, varying study designs, as well as the systematic methods utilized in differing types of data analyses. Though this course will introduce research processes across the academic spectrum, quantitative analysis of both small and large data sets will be emphasized. Therefore, students will learn about basic statistical analyses and will be introduced to the emerging worlds of data science and social media analytics. Students will also consider related topics such as data visualization or research presentations.

Take both:

  • Independent Study, Directed Research, Internship or ESOC 480: Digital Engagement (3 units)
  • ISTA 498: Capstone Project (3 units)

BSIS students are required to take 18 units from a minor or dual major.

Elective courses may be needed to reach the 120-unit graduation requirement, of which 42 units must be upper-division (300-level or above) coursework.

View All School of Information Undergraduate Courses

NOTICE: The Information Science and Technology degree has been renamed Information Science, with two available emphasis areas: Data Science or Interactive and Immersive Technologies.

Students declaring a new major during Fall 2021, post Seven Week 2 and onwards, will be placed in the Information Science 2021-22 catalog and must choose one Emphasis. Students who had previously declared Information Science and Technology can continue to follow their existing Information Science and Technology catalog.

Students are welcome to discuss the differences in catalog and name with their academic advisor.

Ready to shape the future of information?

Learn more about the Bachelor of Science in Information Science by contacting us at ischool-ugrad@arizona.edu, or review the admissions process and begin your application now.

If you are a current UArizona student, learn more about declaring a major, minor or certificate.

Start Your Application