Mimir, Keeper of the Well of Wisdom
Model Evaluation and Interpretation with Generative AI
https://app.pluralsight.com/library/courses/model-evaluation-interpretation-generative-ai
Year : 2026
Language : English
Level : Intermediate
Category :
Subcategory :
Duration : 58m
Lectures : 10
Rating : 0/5
Students :
INSTRUCTOR(S)
Gihad Sohsah
Gihad Sohsah is an AI engineer, educator, and entrepreneur with over
13 years of experience in applied machine learning and deployable AI
systems. She has led the development of scalable AI pipelines,
generative 3D solutions, and computer vision applications across
industries including media, education, fintech, robotics, and digital
twins. Passionate about bridging technical depth with clear
communication, Gihad creates educational content that transforms
complex AI concepts into practical, real-world skills. Her work
focuses on non-hallucinating AI, data efficiency, and trustworthy
model design. As a Pluralsight Author, she aims to empower learners to
move beyond experimentation and build AI systems that perform reliably
in production environments.
HEADLINE
Machine learning models can be powerful but hard to interpret. This
course will teach you how to use Generative AI to evaluate, interpret,
and communicate model performance with clarity and fairness.
WHAT YOU'LL LEARN
REQUIREMENTS
WHO IS THIS COURSE FOR
DESCRIPTION
Many machine learning models perform well but remain difficult to
interpret and explain. In this course, Model Evaluation and
Interpretation with Generative AI, you’ll learn to use generative AI
to evaluate, interpret, and communicate model performance effectively.
First, you’ll explore how generative AI can generate and interpret
evaluation metrics for regression and classification tasks. Next,
you’ll discover how AI can explain feature importance, detect bias,
and summarize model behavior in natural language. Finally, you’ll
learn how to use generative AI for error analysis, robustness testing,
and fairness assessment. When you’re finished with this course, you’ll
have the skills and knowledge of model evaluation and interpretation
needed to make your models more transparent, trustworthy, and
explainable.
LINKS
None
COURSE CONTENT
[1] Evaluating and interpreting model performance with generative AI
1. When metrics don't tell the whole story [5:24]
2. Understanding model behavior and comparing versions [3:54]
3. Turning numbers into narratives with generative AI [4:41]
4. Choosing the right evaluation metrics with generative AI [6:03]
[2] Detecting and mitigating model bias with generative AI
5. Discovering bias in model predictions [3:50]
6. Explaining bias and fairness visually [7:09]
7. Mitigating bias and testing improvements [7:33]
[3] Error analysis and model debugging with generative AI
8. Finding patterns in model errors [4:39]
9. Confidence calibration and reliability testing [7:16]
10. Probing model robustness and communicating limitations [7:42]
DATES
Published : 2026-04-22
Last Updated : 2026-04-22
If you fear the truth, dont come to my well.