Artificial Intelligence Capstone Project

Catalog description

Students will identify stakeholders and collaborate with one another to create solutions using AI. Effective communication and presentation skills will be emphasized as students share project progress with each other and stakeholders. Throughout the course, students will develop and refine machine learning models, ensuring they are robust and production-ready with quality assurance practices. They will design and maintain scalable data infrastructure, incorporating MLOps practices to ensure fault tolerance and efficiency. The course will also cover the importance of analyzing tradeoffs in production systems, focusing on aspects such as cost, latency, and explainability. Students will leverage advancements in technology to enhance their projects while ensuring compliance with safety, security, privacy, fairness, and Responsible AI principles. By the end of the course, students will have the skills to build, deploy, and maintain high-quality AI systems that can be tested, monitored, and updated effectively.