LEARNING PATH / 05 OF 06
AI
Undergraduate
Move from using models to engineering reliable AI products, ready for the real world.
Path overview and starting requirements
⊞
Build the systems behind the magic.
PROPOSED CURRICULUMDates, duration, pricing, and delivery format will be confirmed before enrollment.
Ask about this path ↗A GOOD STARTING POINT IF…
Programming confidence, including Python foundations, and readiness to work with data and mathematical ideas.
A pathway to grow into. Readiness matters more than a label.
WHAT YOU’LL EXPLORE
Four building blocks.
A world of possibility.
LLMs, RAG & agent systems
AI engineering & deployment
Internship preparation & capstones
AN EXAMPLE PROJECT
Deploy a document assistant with retrieval and evaluations.
Start small, show how it works, test its limits, and explain what you would improve next. This is an example learning brief, not a completed student project.

WORK TOWARD BEING ABLE TO…
Build a retrieval-based application and evaluate its answers.
Work with models, datasets, and deployment decisions.
Present a capstone with evidence of reliability and clear limitations.
GO FURTHER, TOGETHER
Ready for this
chapter?
Tell us where you are now and what you want to learn.