Master the techniques for creating transparent AI systems in "Techniques For Building Interpretable AI Models Essentials," designed for AI practitioners and researchers.
Learning Objectives
- Understand the key concepts of model interpretability and transparency.
- Explore advanced methods for creating interpretable AI models.
- Develop skills to balance model performance and interpretability.
- Analyze the trade-offs between complex and interpretable models.
- Apply interpretability techniques in real-world machine learning projects.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.