Foundations in Artificial Intelligence Certificate
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The Foundations in AI Certificate is a three-course program designed for professionals seeking to understand, apply, and ethically implement artificial intelligence in their fields. With no coding or prior technical background required, this certificate provides an accessible yet rigorous pathway into the world of AI and machine learning. Learners gain both conceptual and practical expertise, using leading-edge AI tools and frameworks to drive data-informed decision-making and responsible innovation. The program emphasizes ethical and human-centered approaches to AI application across industries such as business, healthcare, government, and education.
Applicants must meet the general GRADUATE REQUIREMENTS.
Please refer to the University Catalog for Tuition and Fees.
This program is designed to be completed in about 6 months.
For more information about program requirements, completion, and licensure, refer to the University Catalog.
View the course schedule for this program: AI CERTIFICATE Plan.
CORE REQUIREMENTS :
The Foundations in AI Certificate is a three-course program designed for professionals seeking to understand, apply, and ethically implement artificial intelligence in their fields. With no coding or prior technical background required, this certificate provides an accessible yet rigorous pathway into the world of AI and machine learning. Learners gain both conceptual and practical expertise, using leading-edge AI tools and frameworks to drive data-informed decision-making and responsible innovation. The program emphasizes ethical and human-centered approaches to AI application across industries such as business, healthcare, government, and education.
This course focuses on hands-on experience with popular no-code and low-code AI tools that support business, research, and operational decision-making. Students will explore AI-powered platforms such as ChatGPT, Microsoft Copilot, Google AutoML, and RapidMiner to perform sentiment analysis, predictions, classifications, and generative content tasks. Emphasis is placed on tool selection, interpreting outputs, and understanding the limitations of black-box models. Students will complete guided labs and real-world mini projects using AI tools relevant to their field of study.
In this capstone-style course, students will apply their knowledge of AI concepts and tools to design an ethical and impactful AI solution in a domain of interest. Topics include responsible AI development, algorithmic bias, transparency, human-AI collaboration, and data governance. Students will engage with case studies and frameworks for ethical design and risk assessment. The course culminates in a guided project proposal for a real-world AI solution, emphasizing responsible innovation and human-centered design.