Project report
Explain business context, user problem, AI solution, testing results, limitations, and next improvements.
AI Portfolio Guide
AI Portfolio for University Applications
For university applications, the value is not saying that a student learned AI. The value is showing how the student found a problem, used AI, took a role, delivered work, and explained the process clearly.
A useful AI project portfolio should include project context, problem definition, solution design, student contribution, a working demo, process records, feedback, and reflection.
Demo video
Use 2-3 minutes to show how the system works and what the student contributed.
Contribution statement
Clarify the student's role, tasks completed, problems faced, and improvements made.
Interview story
Turn the project into a concrete story: why it mattered, how it was built, what was learned, and what comes next.
Why is a real project stronger than a course certificate?
A certificate shows attendance. A real project shows how a student understood a problem, worked with a team, delivered something, and created evidence that can be shown.
How AI Project Lab helps students build portfolio evidence
Students complete milestone tasks around Canadian business scenarios, then package the work into reports, demos, contribution records, mentor feedback, and application-ready stories.