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CODE: NAI15
DURATION: 3 Days | 5 Days | 10 Days
CERTIFICATIONS: CPD
This course explores the critical concepts of fairness, transparency, and explainability in AI systems. The course includes practical tools and frameworks for measuring fairness and generating model explanations, equipping participants with the skills to build ethical and trustworthy AI applications. Participants will learn how biases are introduced into algorithms, how to detect and reduce them, and how to build models that are interpretable and accountable.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Know about the sources and impact of bias in AI systems.
Apply fairness metrics to evaluate model behavior.
Use tools to explain model predictions and decisions.
Design AI systems with transparency and ethical alignment.
Communicate AI decisions clearly to non-technical audiences.
Build trust in AI systems through interpretable design.
Align model development with regulatory and ethical standards.
At the end of this course, you’ll understand:
This course is designed for data scientists, AI/ML engineers, technical leads, compliance officers, product managers, researchers, and policy advisors. All categories of professionals working on AI systems where transparency, accountability, and fairness are required or regulated, such as in finance, healthcare, human resources, or government, will find the course as a useful guide in their operations.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
