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BCS AI19 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Machine Learning Fundamentals | 25% | - Basic ML process: data, training, validation, deployment - Definition and difference from traditional programming - Overview of ML techniques |
| Topic 2: Introduction to Artificial Intelligence | 25% | - Terminology and core concepts - Types of AI: Narrow/Weak AI vs General/Strong AI - Definition and history of AI |
| Topic 3: Challenges, Risks and Ethics | 20% | - Ethical, legal and social considerations - Technical and operational challenges - Bias, transparency and accountability |
| Topic 4: Benefits and Applications of AI | 20% | - Innovation opportunities - Productivity and efficiency gains - Business and industry use cases |
| Topic 5: Future of AI and Human Collaboration | 10% | - Impact on work and society - Human-AI interaction models - Responsible AI development |
