AI Assurance Audit Awareness Session (Delhi)
Ensuring Trustworthy Systems
Ampcus Cyber is hosting a one-day AI Assurance Audit Awareness Workshop that transforms complex AI governance into practical steps. Learn how to audit systems, assess bias, and ensure compliance - equipping your organization with the clarity and confidence to build trustworthy, transparent, and resilient AI.
In Partnership with
27th September, 2025
09:00 AM - 05:00 PM (IST)
New Delhi
Fee & Registration
₹1100
Non-ISACA Chapter
Members
₹500
ISACA Chapter
Members
Unlock Benefits
6 CPE
Credits
Certificate of Completion
Training Materials
Real-world Case Studies
Network with Industry Peers
Who Should Attend?
Why Attend AI Assurance Audit Session?
Why CAISS Workshop Is Important?
Stay Relevant: In a rapidly changing digital landscape, staying updated on the latest security trends is crucial.
Practical Learning: Hands-on workshops and real-world case studies ensure practical application of AI in cybersecurity.
Networking Opportunities: Connect with industry experts and peers to exchange insights and best practices.
Career Advancement: Earn a prestigious certification that demonstrates your expertise in the intersection of AI and cybersecurity.
Trainers
Salil Dighe
Senior Cybersecurity Consultant
at Ampcus Cyber
(Veteran CISO | 20+ Yrs Experience | CISSP)
Nikhil Raj Singh
Chief Strategy Officer
at Ampcus Cyber
(Cybersecurity Leader | PCI QSA | PCI Forensic Investigator | HITRUST CCSFP)
What Will You Learn?
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Presentation and discussion on AI assurance principles and lifecycle
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Case Study 1: AI in Healthcare Diagnostics
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Overview of audit frameworks and risk management
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Exercise 1: Identifying Risks
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Discussion on model development, validation, and bias
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Case Study 2: Bias in Hiring Algorithms
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Exercise 2: Bias Detection
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Topics on data quality, governance, privacy, and security
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Case Study 3: Data Breach in AI System
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Exercise 3: Data Governance Plan
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Techniques for explainable AI and stakeholder communication
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Case Study 4: Explainable AI in Finance
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Exercise 4: Explainability Assessment
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Summary and key takeaways
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Q&A and discussion
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Feedback and next steps