Curriculum Requirements
Minor in Artificial Intelligence
Minor Requirements
| Required Courses | Credits: | |
| CSCI 202 | Introduction to Computer Science and Artificial Intelligence | 3 |
|
This course provides a comprehensive introduction to computer science, covering core concepts such as hardware systems, programming essentials, algorithms, data handling, and the basics of artificial intelligence. It is designed for both technical and non-technical majors interested in gaining a foundational understanding of computer science and AI. Through a blend of lectures, hands-on projects, and problem-solving exercises, students will acquire the skills and knowledge necessary to pursue further studies in computer science, engineering/technology programs, or a minor in Artificial Intelligence. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| PHIL 315 | AI Ethics and Societal Impact | 3 |
|
This course delves into the ethical, social, and legal challenges posed by the development and implementation of artificial intelligence technologies. Through a combination of lectures, readings, discussions, and projects, students will examine issues such as privacy, bias, fairness, autonomy, and the societal impacts of AI. The goal is to equip students with the knowledge and skills to critically analyze and engage with the ethical dimensions of AI technologies in their future professional practices. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| Total: 6 Credits | ||
| Substitutions with courses taken in the student's major are allowed with permission of the chair. | ||
| Elective Courses (select three) | Credits: | |
| ARCH 326 | Foundations of Generative Artificial Intelligence and Creativity | 3 |
|
This course delves into Generative AI, exploring its theoretical underpinnings, applications, and creative possibilities. It covers basic concepts, algorithms, and historical context in the first part, emphasizing AI's ethical dimensions. The second part focuses on how AI shapes creative fields like arts and design, addressing its potential in addressing societal challenges. By combining theory with hands-on projects, the course offers students a holistic understanding of Generative AI's role, fostering critical thinking and enhancing their employability. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| ARCH 328 | Generative Artificial Intelligence, Design, and Fabrications | 3 |
|
This course on Generative Artificial Intelligence explores implications within robotics, digital fabrication, and material intelligence, contextualized in regard to the broader realm of design and creative practice. It is designed to bridge the gap between advanced computational technologies and creative applications, showcasing how AI can revolutionize design processes, material innovation, and robotic automation. The course does not limit discussions to technological aspects alone but expands to include the broader creative and design implications of generative AI. It aims to understand how AI influences aesthetic decisions, the ideation process, and the future of design professions. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| BUSI 320 | Data Visualization and Interpretation with AI integration | 3 |
|
Prerequisite: Prerequisites: CSCI 202 or Chair Permission This course equips students with the skills to utilize artificial intelligence to enhance data visualization and interpretation capabilities. The course focuses on leveraging AI to automate the generation of insights, utilize natural language processing for intuitive data exploration, and effectively visualize high-dimensional data. Students will learn to communicate complex data-driven insights clearly and effectively, facilitating strategic decision-making in various business contexts. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| BUSI 420 | Business Intelligence and AI for Decision Making | 3 |
|
Prerequisite: Prerequisites: CSCI 202 or Chair Permission This course explores the integration of artificial intelligence (AI) with traditional business intelligence (BI) techniques to enhance strategic decision-making capabilities. Students will learn to use AI-powered tools for data mining across domains and to analyze and predict business outcomes such as sales, market trends, customer behavior, and employee engagement. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| BUSI 421 | Optimization and Process Analytics | 3 |
|
Prerequisite: Prerequisites: CSCI 202 or Chair Permission This course introduces students to the principles of optimization and process analytics with a focus on their practical applications. Students will learn to leverage AI to develop, refine, and solve optimization models more effectively. The course emphasizes the integration of AI capabilities with traditional optimization methods to enhance decision-making processes across various business domains. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| CSCI 316 | Machine Learning and Data Mining Applications | 3 |
|
This introductory course is designed to explore the transformative world of Machine Learning and Data Mining for a general audience. It covers fundamental principles behind machine learning algorithms and data mining processes, interpretation of data patterns and predictions, and ethical considerations in automated data analysis. The course aims to provide students with foundational knowledge and skills in machine learning and data mining, equipping them to make informed decisions in their careers. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| CSCI 317 | Introduction to Generative AI and Large Language Models | 3 |
|
This course introduces the dynamic field of Generative Artificial Intelligence and Large Language Models (LLMs), focusing on their development, functionality, and impact on various sectors. Designed for a general audience, this course covers the principles behind AI generation, including the design and function of models like the Generative Pre-trained Transformer (GPT). Through a mix of lectures, interactive sessions, and practical exercises, students will explore the broad applications and ethical considerations of these technologies. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| HSCI 315 | AI in Healthcare | 3 |
|
Prerequisite: Prerequisites: MGMT 101 or MGMT 102 This course explores the integration of Artificial Intelligence (Al) into the health professions, emphasizing the understanding, application, and implications of Al technologies in diverse healthcare settings, including healthcare education and patient care. Additionally, students will examine the historical and current use of Al, its impact on Electronic Medical Records (EMR), and the ethical, practical, and technological challenges associated with its implementation. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
||
| Total: 9 Credits | ||
| Total Program Required Credits = 15 |