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