Core Courses

AI 010: INTERDISCIPLINARY REFLECTIONS ON ARTIFICIAL INTELLIGENCE, 3 credit hrs.
This course will introduce students to artificial intelligence possibilities. Specifically, this course will present reflections and observations from interdisciplinary guest speakers each week in a seminar format. Students will be exposed to a number of different areas and reflect on what they learn.

AI 042: ARTIFICIAL INTELLIGENCE, 3 credit hrs. or PHIL 130: MINDS, BRAINS, AND COMPUTERS, 3 credit hrs.

• A1 042: ARTIFICIAL INTELLIGENCE
  • This course will explore the past, present, and future of Artificial Intelligence (AI). We will begin by looking at the initial aims of AI and the theoretical and technological developments that made AI look like a genuine possibility (and survey some of the early successes and failures of that research program). We will then consider the current state of AI and the way future developments may (or may not) have a significant impact on society and self. Our investigation of these topics will be informed by scholarly works (e.g. philosophy, computer science, and social science) and works of fiction (e.g., short stories and films).
• PHIL 130: MINDS, BRAINS, AND COMPUTERS
  • An introduction to philosophy of mind, focused on the nature of intentionality and consciousness, the relationship between mental and physical states, and the possibility of artificial intelligence.

PSY 001: INTRODUCTION TO PSYCHOLOGY, 4 credit hrs. or NCSI 001: INTRODUCTION TO NEUROSCIENCE, 3 credit hrs.

• PSY 001: INTRODUCTION TO PSYCHOLOGY
  
  • A survey of contemporary methods and approaches to the science of behavior, which may include such topics as methodology, physiology, developmental and social psychology, sensation, perception, learning, intelligence, personality, and mental illness and treatment. Psychology lab is required. The laboratory uses experiments, discussions, demonstrations and other activities to complement the materials in the lecture. Psychology 001 is required for majors and minors. AOI: Scientific Literacy/Life Science
• NCSI 001: INTRODUCTION TO NEUROSCIENCE
  
  • This course explores the core concepts of the interdisciplinary field of neuroscience. Emphasis is placed on cellular mechanisms, neurotransmission, human brain anatomy, sensory physiology, the motor system, emotion, sleep, cognitive neuroscience, and psychopathology. Although a comparative perspective is taken, human neuroscience is emphasized. This course serves as preparation for many advanced neuroscience courses. AOI: Scientific Literacy/Life Science

AI 036: NATURE OF INTELLIGENCE AND RELATIONSHIP TO ARTIFICIAL INTELLIGENCE, 3 credit hrs. or PSY 125: COGNITIVE PSYCHOLOGY, 4 credit hrs.

• AI 036: NATURE OF INTELLIGENCE AND RELATIONSHIP TO ARTIFICIAL INTELLIGENCE
  
  • This course will explore contemporary and historical perspectives on learning and intelligence. Drawing from philosophy, psychology, and neuroscience, we will explore common themes and open-questions regarding the natures of learning and intelligence. Interactions between technological development (e.g., artificial intelligence) and views about learning and intelligence will be explored. AOI: Critical Thinking 
• PSY 125: COGNITIVE PSYCHOLOGY
  
  • The basic concepts and findings of cognitive psychology, including the topics of perception, attention, learning, memory, language, categorization, imagery, judgment and decision-making, and problem-solving. Cognition will be discussion from the perspectives of information processing and cognitive neuroscience. With laboratory. Prereq.: [(PSY 001 or NCSI 001 or AP 039) and PSY 011 or (BIO 140 or STAT 071 or STAT 072) and PSY 013]

CS 083: Digital Ethics 3 credit hrs.
This course increases understanding of issues related to ethics, professional conduct and social responsibility as they arise in Computer Science and applications of Information Technology. Additionally, the course serves to develop 1) the ability to think clearly; 2) habits of professional responsibility and behavior; and 3) effective writing and presentation skills. Students are exposed to the history of the discipline from a social point of view, and to various frameworks from which ethical and professional decisions must be made within the discipline. Prereq.: Sophomore, Junior, or Senior standing required. AOI: Values and Ethics

IS 083: IT LEGAL AND ETHICAL ISSUES, 3 credit hrs.
This course provides an overview of ethical and legal issues associated with business information technology usage, data collection, data sharing, and data-driven decision making. Topics include ethical and legal perspectives on privacy and information rights, organizational computer usage policies, cybercrime, and intellectual property. AOI: Values and Ethics

AI 051 / ENG 82: AI IN FICTION, 4 credit hrs. or SCSS 135: TECHNOSCIENCE CULTURE AND PRACTICE, 3 credit hrs.

• AI 051 / ENG 82: AI IN FICTION
  
  • This course examines our past and present cultural beliefs and anxieties about artificial intelligences, looking at popular works that have spoken to audiences’ fears of, and hopes for, intelligent machines that interact with humans and participate in human life. From calculating murderers (eg: HAL 9000) to protective companions (eg: Baymax), how have we viewed these artificial persons, and what have imagined becomes of natural, biological humans who live lives integrated with AI? AOI: Written Communication
• SCSS 135: TECHNOSCIENCE CULTURE AND PRACTICE
  
  • This course offers a historical and theoretical overview of the interdisciplinary field called science studies or the social studies of science and technology as it has emerged mostly since the 1970s in the United States and the United Kingdom. The focus moves beyond looking for so-called "social factors" or "forces" thought to influence the social organization of science and scientific work to taking the very contents and practices of science as the objects of critical examination, including the very study thus constituted.

STAT 071: STATISTICS I, 3 credit hrs.
An introduction to descriptive and inferential statistics; frequency distributions; measures of central tendency and spread; confidence intervals; large and small sample tests of significance; probability; and binomial and normal distributions. Prereq.: MATH 020 or MATH 028 or equivalent. AOI: Quantitative Literacy

STAT 108: MODERN REGRESSION, 3 credit hrs.
Prediction is often at the heart of issues faced by companies and scientific disciplines alike. This is an applied regression course using R (but assuming no prior programming experience) with an emphasis on prediction and decision making. Course will start with simple linear regression and multiple linear regression, discussing statistical assumptions and diagnostics. This will set the stage for discussions on modern model selection methods aimed at improving prediction such as ridge regression, lasso, and adaptive lasso. Course will introduce nonparametric regression, regression trees, random forests and cross validation methods for model comparison as well as models for time series data. Throughout, an emphasis will be placed on the strengths and limitations of what you can (can’t) do with the methods and what you can (can’t) learn from the methods. Prereq.: STAT 071

PHIL 128: LANGUAGE AND REALITY, 3 credit hrs. or ENG 139: LANGUAGE AND LOGIC, 3 credit hrs.

• PHIL 128: LANGUAGE AND REALITY
  
  • An introduction to philosophy of language, linguistics, and semiotics focused on the issue of linguistic relativism, i.e., whether languages are significantly different, and if so, whether they shape significantly different views of reality. Examines evidence both in support of and against linguistic relativism, and then uses this evidence as a means of addressing the relationship between language and reality.
• ENG 139: LANGUAGE AND LOGIC
  
  • Content-based course with discussion and creative projects. This course looks at the ways scholars and writers have attempted to systematize the English language through descriptive linguistics, prescriptive grammar rules, categories of rhetorical persuasion, syllogism, metaphor, and narrative structures, and asks how reasonable language is? Additional questions may include: why is natural human language such a challenge for machines? What attempts have been made to systematize language, and why is language resistant to these attempts? AOI: Critical Thinking

CS 065: INTRODUCTION TO COMPUTER SCIENCE I, 3 credit hrs.
Algorithms, programming, program structures and computing systems. Debugging and verification of programs, data presentation. Computer solution of problems using a high- level language. Prereq.: 4 years of high school Mathematics or MATH 020. AOI: Critical Thinking; Information Literacy

CS 066: INTRODUCTION TO COMPUTER SCIENCE II, 3 credit hrs.
Continuance of CS 65 using a block-structured language and emphasizing data abstraction. More general data structures and alternative implementations of them are used in programs, Sorting, searching and tree traversal algorithms are used and analyzed. Provides preparation for further study in computer science. Prereq.: CS 065 or equivalent.

CS 143: ARTIFICIAL INTELLIGENCE, 3 credit hrs.
Introduction to the theory, tools and methods of artificial intelligence. Topics include knowledge representation, predicate calculus, basic data structures, and problem-solving strategies. A symbol manipulation language is used. Computer science aspects of artificial intelligence are emphasized. Applications from areas such as natural language understanding, vision or expert systems are examined. Prereq.: CS 066

CS 167: MACHINE LEARNING, 3 credit hrs.
This course introduces approaches to developing computer programs that learn from data. Both foundational and contemporary machine learning algorithms will be covered in the context of a variety of data and problem types. Specific topics will vary but may include artificial neural networks, decision trees, instance-based learning, Bayesian learning, support vector machines, hidden Markov models, reinforcement learning, and natural language processing. Students will develop their own implementations of the algorithms as well as utilize modern machine learning software and programming libraries. Prereq.: CS 066

IS 147: HUMAN FACTORS IN IS, 3 credit hrs. or ART 150: HISTORY OF HUMAN-CENTERED DESIGN, 3 credit hrs.

• IS 147: HUMAN FACTORS IN IS
  
  • This course explores current trends in systems development related to human computer interaction. Specifically, this course focusses on information about human behavior, cognition, abilities and limitations, and other characteristics relevant to interaction with information systems. Specific strategies which apply these concepts in an effort to improve system usability will be explored.
• ART 150: HISTORY OF HUMAN-CENTERED DESIGN
  
  • This is an experimental lecture course that takes a broad overview of how the human body has influenced the built environment. Diving into architecture, industrial design, and graphic design we will connect how designers have used human measurements and needs to create innovative objects, spaces, and experiences. Starting in 1490, we will trace the origins and pioneers of human-centered design and follow the impacts on the built environment to the present. This 3-credit hour course in design history will require reading, writing, discussion, field trips, and hands-on studio work. AOI: Artistic Experience; Historical Foundations

IS 161: INFORMATION SYSTEMS ANALYSIS AND DESIGN, 3 credit hrs.
This course provides an introduction to strategies and technologies for analyzing business processes and systems in an organization. Course topics include overview of systems development methodologies and project management, systems planning (project selection and initiation and requirements discovery), systems analysis (Process and logic modeling), systems design (prototyping, rapid application development, and agile development), and systems implementation (quality assurance and maintenance). Prerep.: IS 107 or CS 066

AI 190: ARTIFICIAL INTELLIGENCE PRACTICUM, 3 credit hrs.
The purpose of this capstone is for students to be able to apply their artificial intelligence knowledge through the creation and reflection of an artificial intelligence product.  Case studies will also be utilized for reflection.