CIS 5980 Artificial Intelligence Capstone

Short Description

This hands-on capstone course in the MSE in AI Online program provides students with the opportunity to design, develop, and deploy AI-driven applications that serve as portfolio-ready demonstrations of their skills. Students will apply techniques and concepts learned throughout the program to tackle open-ended, practical problems, projects may be team-based. Students will identify a meaningful AI application idea, scope the project, and define deliverables. Projects may include - but are not limited to - LLM-based applications, computer vision systems, reasoning agents, AI for scientific discovery, or multi-modal AI experiences. Students are encouraged to select projects that integrate multiple AI techniques and reflect the full development cycle, from ideation to deployment. As part of this cycle, students will be expected to work with open source software and models, continue training or fine-tune models for their application, and robustly evaluate their systems using existing benchmarks or custom-built evaluation metrics that they create as part of the capstone. Weekly office hours and check-ins will provide a forum to discuss technical and design challenges, review progress, and share feedback on implementation and user experience. Instructor and TAs will guide students in best practices for system design, model selection and fine-tuning, data management, evaluation, and ethical considerations in AI deployment. The course will culminate in a public-facing website showcasing the student projects, and a final presentation where students present and demo their applications to peers and faculty. These portfolio demos will be polished and professional, making them suitable to share with potential employers as evidence of applied AI expertise.

Portfolio Building Course

No

Pre-Requisites

Required: CIS 5210, CIS 5300, and either ESE 5410 or ESE 5420. Recommended: Students should be nearing the end of their program and/or should have the required background for their proposed project in order to register. Please note that registration for this course requires program approval. Please note, as a course expense, students will need to subscribe to an AI service for the duration of Capstone. The cost is estimated to be approximately $50/month.

Content

This hands-on capstone course in the MSE in AI Online program provides students with the opportunity to design, develop, and deploy AI-driven applications that serve as portfolio-ready demonstrations of their skills. Students will apply techniques and concepts learned throughout the program to tackle open-ended, practical problems, projects may be team-based.

Students will identify a meaningful AI application idea, scope the project, and define deliverables. Projects may include – but are not limited to – LLM-based applications, computer vision systems, reasoning agents, AI for scientific discovery, or multi-modal AI experiences. Students are encouraged to select projects that integrate multiple AI techniques and reflect the full development cycle, from ideation to deployment. As part of this cycle, students will be expected to work with open source software and models, continue training or fine-tune models for their application, and robustly evaluate their systems using existing benchmarks or custom-built evaluation metrics that they create as part of the capstone.

Weekly office hours and check-ins will provide a forum to discuss technical and design challenges, review progress, and share feedback on implementation and user experience. Instructor and TAs will guide students in best practices for system design, model selection and fine-tuning, data management, evaluation, and ethical considerations in AI deployment.

The course will culminate in a public-facing website showcasing the student projects, and a final presentation where students present and demo their applications to peers and faculty. These portfolio demos will be polished and professional, making them suitable to share with potential employers as evidence of applied AI expertise.

Course Creators

• Chris Callison-Burch