Track Details
AI Trainer
Overview
Evaluate models: accuracy vs precision/recall, confusion matrix, error analysis, and bias mitigation; apply to "AI for Good".
8 Levels
40 Assessment
Certification partners
In collaboration with University of Delaware and Academy of Leeds, aligned to their education quality frameworks.
Modules
Levels
Model Testing Lab
Metrics, confusion matrix, validation ideas.
20 Hours
20 Lectures
8 Assessment
Error Analysis
Collect confusion cases; fix data.
20 Hours
20 Lectures
8 Assessment
Bias & Fairness
Detect and reduce bias; document risks.
20 Hours
20 Lectures
8 Assessment
AI for Good Challenge
Design, test, and present impact.
20 Hours
20 Lectures
8 Assessment
Track Projects
- Which Model Wins?: Students create a comparison board to evaluate different AI models using various metrics.
- Bias Busters: Students identify bias in datasets and rebuild them to create fairer AI systems.
- Safety Card: Students develop documentation that identifies potential risks and safety measures for AI systems.
Capstone
AI for Good Demo: Students develop an AI solution addressing a social challenge and test it with actual community members. This project showcases their ability to create ethical AI applications with real-world impact.
Work smart not hard
