Understand the foundations of trust and transparency in AI with "Explainable AI and Trust in Machine Learning Training," focusing on interpretability and ethical AI practices.
Learning Objectives
- Understand the principles of explainable AI and its importance in trust-building.
- Analyze techniques for interpreting machine learning models and their predictions.
- Explore case studies demonstrating the impact of explainable AI in various industries.
- Develop skills to integrate explainability into AI workflows and systems.
- Evaluate regulatory and ethical considerations related to explainable AI.
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.