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BCS AI19 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Introduction to Artificial Intelligence | 25% | - Types of AI: Narrow/Weak AI vs General/Strong AI - Definition and history of AI - Terminology and core concepts |
| Machine Learning Fundamentals | 25% | - Overview of ML techniques - Basic ML process: data, training, validation, deployment - Definition and difference from traditional programming |
| Benefits and Applications of AI | 20% | - Innovation opportunities - Productivity and efficiency gains - Business and industry use cases |
| Future of AI and Human Collaboration | 10% | - Impact on work and society - Responsible AI development - Human-AI interaction models |
| Challenges, Risks and Ethics | 20% | - Bias, transparency and accountability - Technical and operational challenges - Ethical, legal and social considerations |
