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CODE: NAI16
DURATION: 3 Days | 5 Days | 10 Days
CERTIFICATIONS: CPD
This course explores how to build AI systems that are transparent, fair, and accountable. Participants will learn the principles and techniques for auditing AI models, detecting and mitigating bias, and improving model interpretability. By using real-world datasets and tools like SHAP, LIME, and fairness libraries, participants will gain practical experience in evaluating AI systems for ethical integrity and regulatory compliance. The course emphasizes responsible AI development to support trustworthy decision-making across sectors.
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:
Learn the ethical and legal foundations of trustworthy AI.
Conduct AI audits to evaluate fairness, accountability, and transparency.
Detect and mitigate data and algorithmic bias.
Use interpretability tools to explain AI predictions.
Design AI systems aligned with regulatory frameworks and ethical guidelines.
Communicate model decisions clearly to technical and non-technical audiences.
Apply best practices for documenting and validating AI models.
At the end of this course, you’ll understand:
This course is designed for data scientists, machine learning engineers, compliance officers, AI researchers, policy makers, risk managers, and anyone involved in developing or deploying AI solutions. It is especially relevant for professionals working in high-stakes environments such as finance, healthcare, human resources, and public services where AI outcomes must be explainable and fair.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
