Unlock the power of next-generation AI by mastering evaluation techniques for models that integrate vision, audio, and language capabilities. This course transforms your ability to systematically assess multimodal AI performance and ensure ethical deployment at scale. You'll master cross-modal evaluation metrics like FID, CLIP scores, and recall@k while developing expertise in bias detection and interpretability assessment using LIME and SHAP techniques. By completing this course, you'll confidently evaluate complex AI systems, identify potential ethical risks, and implement governance frameworks that ensure fair and transparent multimodal AI deployment. This unique course combines technical evaluation expertise with ethical AI governance, preparing you for the enterprise reality where performance and responsibility must coexist seamlessly.

Evaluate and Apply Ethical AI Models

Evaluate and Apply Ethical AI Models
This course is part of Building Trustworthy AI Specialization

Instructor: John Whitworth
Access provided by Interbank
Recommended experience
What you'll learn
Cross-modal evaluation requires specialized metrics that assess semantic alignment and joint reasoning capabilities across different data modalities.
Ethical AI assessment is a systematic process involving quantitative bias measurement and interpretability analysis using standardized frameworks.
Enterprise AI deployment success depends on balancing performance optimization with ethical governance and continuous monitoring.
Model interpretability through LIME and SHAP analysis provides transparency essential for responsible AI system deployment.
Details to know

Add to your LinkedIn profile
4 assignments
January 2026
See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate

There are 2 modules in this course
Learners will master cross-modal evaluation metrics to systematically assess multimodal AI model performance in enterprise environments.
What's included
3 videos1 reading1 assignment1 ungraded lab
Learners will master systematic approaches to assess model bias and apply ethical AI guidelines for responsible multimodal AI deployment.
What's included
2 videos1 reading3 assignments
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor

Offered by
Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
Explore more from Data Science

Johns Hopkins University

AI CERTs

Alex Genadinik


