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