6 courses with the subject GAI, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
GAI 101INTRODUCTION TO AI AND GENERATIVE AI
In this course, students will also learn foundational ethical considerations, including bias, privacy, and intellectual-property considerations. The course prepares learners to use GenAI tools safely and effectively in academic, workplace, and personal settings. Students will have access to a balanced collection of written resources, recorded lectures, podcasts, and current events, and will participate in a series of activities using GenAI, structured online discussions, labs, case studies, and projects. Credit Hours: Lecture-1.5, Lab-1.5, Credits-3 Prerequisite(s): None
Through hands-on exercises, students will gain experience working with structured and unstructured information and learn to identify foundational data quality issues that influence output, responsible data practices, the principles of information literacy, and source evaluation. Through a balanced collection of written resources, recorded lectures, podcasts, and current events, and a series of activities using PENNSYLVANIA INTITUTE OF TECHNOLOGY | COLLEGE CATALOG 2026-2027 156
The course emphasizes collaboration skills, including how to work with teams that employ GenAI tools and resources and how to develop insights from GenAI that you can then share with diverse audiences. Learners are introduced to organizational policies, compliance requirements, and the ethical norms of workplace Gen AI adoption. Through a balanced collection of written resources, recorded lectures, podcasts, current events, and practical activities that will simulate real-world applications, students will build essential skills that they can take directly to the workplace. Credit Hours: Lecture-1.5, Lab-1.5, Credits-3 Prerequisite(s): None
GAI 201GENERATIVE MODELS, MACHINE LEARNING & DATA REASONING
In this course, students will develop new critical data-reasoning skills through activities that include interpreting GenAI model behavior, tracing errors, and evaluating system outputs in context with the situation. Through a balanced collection of written resources, recorded lectures, podcasts, current events, practical activities, and scenario-based projects, students learn to effectively use GenAI tools to support data-driven decision-making in professional, personal, and academic environments. Credit Hours: Lecture-1.5, Lab-1.5, Credits-3 Prerequisite(s): GAI 101, GAI 102, GAI 103
This course will emphasize how to translate raw data into stories that support an individual’s ability to communicate, present to diverse audiences, and drive decision-making in both the classroom and the workplace. Students will explore visualization tools and storytelling techniques to enhance the clarity and impact of a presentation across various settings. This course provides a balanced collection of written resources, recorded lectures, podcasts, practical activities, and scenario-based situations to help students develop these new skills. Credit Hours: Lecture-1.5, Lab-1.5, Credits-3 Prerequisite(s): GAI 101, GAI 102, GAI 103
