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BICSI AIE2.0 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Enablers and Types of AI | - Deep Learning and Neural Networks - Big Data, Generative AI and LLMs - Robotics and AI applications - Machine Learning fundamentals |
| Topic 2: Data for AI Systems | - Data risks and visualisation - Machine Learning process stages - Data definitions and quality characteristics |
| Topic 3: Introduction to AI and Historical Development | - Historical milestones and evolution of AI - Narrow vs General AI - Key terminology and definitions |
| Topic 4: Future of AI and Societal Impact | - Economic and employment impacts - AI roles, career paths and workforce transformation - Future trends and human-AI collaboration |
| Topic 5: AI in Organisations and Governance | - Identifying AI opportunities and use cases - AI project management and lifecycle - Risk management and compliance |
| Topic 6: Ethical and Legal Considerations | - Data privacy and protection - AI governance frameworks including ISO/IEC 42001 - Ethics vs Law in AI context - Bias, fairness, transparency and discrimination risks |



