Last Updated: Aug 21, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Introduction and History of Artificial Intelligence | 15% | - Types of AI and intelligent agents - Benefits and challenges of AI - History and evolution of AI - Definitions and concepts of AI |
| Topic 2: Enablers of Artificial Intelligence | 15% | - Cloud and big data technologies - Data and information requirements - Machine learning fundamentals - Computing infrastructure |
| Topic 3: Finding and Using Data in Artificial Intelligence | 10% | - Data collection and preparation - Data quality management - Data visualization and interpretation |
| Topic 4: Applications of Artificial Intelligence | 15% | - AI use cases across industries - Automation and decision support - Future trends in AI |
| Topic 5: Ethical and Sustainable Human and Artificial Intelligence | 15% | - Responsible AI adoption - Ethical considerations in AI - Sustainability and societal impact - Bias and fairness in AI systems |
| Topic 6: Machine Learning and Other Techniques | 20% | - Unsupervised learning - Reinforcement learning - Neural networks and deep learning - Natural language processing - Supervised learning |
| Topic 7: Legal, Regulatory and Governance Frameworks | 10% | - Data protection and privacy - Legal and regulatory considerations - AI governance principles |
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