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Validate and Explain Your ML Models

This course is part of Train, Tune, & Ship: End-to-End Machine Learning Engineering Specialization

Instructor: ansrsource instructors

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Train, Tune, & Ship: End-to-End Machine Learning Engineering Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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 is 1 module in this course

Module details

This short course helps you validate and explain machine learning models with confidence. You’ll learn practical strategies for using k-fold cross-validation and stratified sampling to estimate performance more accurately, especially when working with imbalanced data. You’ll also explore feature-importance techniques, including SHAP, to understand how your model behaves and how to explain its decisions clearly to technical and non-technical audiences. Through accessible videos, short readings, and hands-on activities, you’ll strengthen your ability to evaluate models beyond a single accuracy score. By the end of the course, you’ll know how to choose the right validation strategy, interpret model explanations, and communicate insights that support responsible deployment in real-world domains like fraud detection and loan approvals.