This course equips you with foundational knowledge and practical skills needed to begin implementing and managing generative AI responsibly in organizational settings. You will examine fine-tuning techniques, address AI system limitations and compliance requirements, and build ethical frameworks to balance innovation with responsibility. By the end, you will be prepared to guide AI implementation decisions that align with business goals, regulations, and ethical standards.
Number of Units: 1.0 graduate level extension credit(s) in semester hours
Who Should Attend: Anyone interested in understanding the current and future direction of AI in business, healthcare, finance and daily life!
Technical Requirements
Once you have enrolled in your course, log in to your account to access the course Welcome Letter, which includes directions on how to access the New Student Orientation and your online course.
At the conclusion of this course participants will be able to:
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Courses offer a convenient, yet rigorous style of learning that allows you to structure your education to suit your schedule while keeping you on pace toward achieving your educational goals.
Online fixed-date courses are delivered virtually but follow a predetermined schedule, requiring students to complete assignments, participate in discussions, and take assessments by specific deadlines—much like a traditional classroom. The key difference is that while traditional courses are conducted in person at set times and locations, online fixed-date courses allow students to engage remotely, offering more flexibility in where they learn while preserving structure and accountability through fixed timelines. (Note: Any scheduled Zoom sessions will be outlined on the class schedule.) These courses have fixed start and finish dates, but as an online student you will have 24/7 online access to your classroom assignments, syllabus and course resources. Instructor feedback is shared along with the graded assignments.
How is the learning structured? Each online fixed-date course is asynchronous, meaning that you can work on your assignments anytime, although you are required to complete the assignments by specific dates. The course is designed with learning modules where all of the content is grouped into weekly assignments. Each module covers one or more topics. Within each of the learning modules, you can expect the following components:
• Module introduction that outlines what you can expect to learn in the module.
• Required readings (textbook, articles, journals, etc.) and presentations (audio and/or video).
• Assignments with due dates (which may include: written assignments, journal entries, research, blogs, etc.) based on the readings and presentations.
• Discussion forum where you answer prompts from the instructor and interact with your classmates.
• Module conclusion to review the topics and what you should have learned.
Typically, there is a final project, paper, or exam due in the last module that culminates all of the topics covered in each of the learning modules. You’ll find that the design of the learning modules has a rhythm to help you manage your time in the course.
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