Master AI model interpretability and transparency techniques using Google Cloud tools for developing explainable AI systems.
Master AI model interpretability and transparency techniques using Google Cloud tools for developing explainable AI systems.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Responsible AI for Developers Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
What you'll learn
Define AI interpretability and transparency concepts
Implement feature-based model explanations
Use Google Cloud tools for model interpretability
Apply transparency techniques to AI models
Skills you'll gain
This course includes:
1 Hours PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This course focuses on AI interpretability and transparency, essential aspects of responsible AI development. Students learn practical techniques for making AI models more explainable and transparent using Google Cloud tools and services. The curriculum covers various interpretability techniques, including feature-based explanations, concept-based explanations, and example-based explanations. Through hands-on labs with Vertex Explainable AI, participants gain practical experience in implementing transparency in both data and AI models.
Course Introduction
Module 1 · 0 Minutes to complete
AI Interpretability & Transparency
Module 2 · 2 Hours to complete
Course Summary
Module 3 · 11 Minutes to complete
Course Resources
Module 4 · 30 Minutes to complete
Instructor
Empowering Businesses with Expert Training from Google Cloud
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Frequently asked questions
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