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IBM C1000-206 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Introduction to Artificial Intelligence | 20% | - Types of AI: Narrow vs General - Definition and history of AI - AI applications and use cases |
| Topic 2: Deep Learning and Neural Networks | 20% | - Applications in computer vision and NLP - Deep learning architectures - Neural network fundamentals |
| Topic 3: AI Tools, Platforms and IBM Solutions | 20% | - Development tools and frameworks - Cloud AI platforms - IBM Watson services overview |
| Topic 4: Machine Learning Basics | 25% | - Data preparation and preprocessing - Supervised, unsupervised, reinforcement learning - Model training and evaluation |
| Topic 5: Ethics, Governance and Future of AI | 15% | - Regulatory compliance and trust - Emerging trends and future directions - Ethical principles and bias mitigation |
