GENERATIVE ARTIFICIAL INTELLIGENCE FOR ENGINEERING APPLICATIONS
Comprehensive coverage of AI-powered chatbots, from understanding generative AI fundamentals to developing sophisticated chatbot applications. Hands-on experience with generative AI tools. Explore retrieval-augmented generation (RAG) techniques. Examine critical aspects such as security, privacy, and memory models. Knowledge of Python [such as COMP SCI 220 or E P D 455 ] strongly recommended.
Prerequisites & course information
Requisites: Graduate/professional standing or declared in Capstone Certificate in Artificial Intelligence for Engineering Data Analytics Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Design and develop a fully functional Generative AI-based chatbot application that can be personalized to the user Audience: Graduate 2. Implement and optimize Retrieval-Augmented Generation (RAG) to enhance chatbot responses Audience: Graduate 3. Integrate memory management systems to improve context retention in chatbot interactions Audience: Graduate 4. Utilize agents to perform specialized tasks within the chatbot framework Audience: Graduate 5. Demonstrate the ability to deploy, test, and maintain chatbot applications in a production environment Audience: Graduate Learning Outcomes: 1. Design and develop a fully functional Generative AI-based chatbot application that can be personalized to the user Audience: Graduate 2. Implement and optimize Retrieval-Augmented Generation (RAG) to enhance chatbot responses Audience: Graduate 3. Integrate memory management systems to improve context retention in chatbot interactions Audience: Graduate 4. Utilize agents to perform specialized tasks within the chatbot framework Audience: Graduate 5. Demonstrate the ability to deploy, test, and maintain chatbot applications in a production environment Audience: Graduate
Sources
- Course catalogue ↗2026-2027