Make your skills useful.
6 practical projects. Real questions. Your own approach.
Put the lessons together in a project you can explain, improve, and share. Each brief includes a synthetic dataset, a starter notebook, and clear success criteria.
Build a workshop request inbox.
Validate incoming requests, identify duplicate deliveries, and keep rejected work visible.
Test a support triage assistant.
Compare keyword rules with simulated model predictions and measure review workload.
Draft answers from approved sources.
Build a small source retrieval flow with access checks, citations, and a no-answer path.
Build a draft approval queue.
Keep approval tied to the reviewed version, reviewer permissions, and expiry.
Recover a failing automation.
Simulate timeouts, replay decisions, retry limits, and an operations digest.
Deliver a workshop automation assistant.
Combine intake, simulated AI, review, recovery, and evaluation in one explainable workflow.
All project datasets are synthetic learning examples. They are for learning and simulation, not operational decisions.
Free, open and run by a nonprofit.
This page is part of AI Automation, a free course of 20 modules and 60 lessons in the engineering.fit( ) Learning Lab. The Learning Lab is built and run by engineering.fit( ), a nonprofit founded by Abdullateef Opeyemi Bakare that helps African engineering students gain research experience. You do not need an account or pay a fee to learn.