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IBM C1000-206 : IBM Artificial Intelligence Fundamentals v1 - Associate

C1000-206

Exam Code: C1000-206

Exam Name: IBM Artificial Intelligence Fundamentals v1 - Associate

Updated: Aug 10, 2026

Q & A: 0 Questions and Answers

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IBM C1000-206 Exam Syllabus Topics:

SectionObjectives
Introduction to Artificial Intelligence- AI concepts and definitions
  • 1. Types of AI systems
    • 2. What is Artificial Intelligence
      - AI applications
      • 1. Real-world use cases
        • 2. Industry adoption scenarios
          Deep Learning and Neural Networks- Deep learning concepts
          • 1. Training deep neural networks
            • 2. Common architectures overview
              - Neural network fundamentals
              • 1. Activation functions overview
                • 2. Perceptrons and layers
                  AI Ethics and Responsible AI- Responsible AI practices
                  • 1. Fairness and accountability
                    • 2. Data privacy considerations
                      - Ethical considerations
                      • 1. Bias in AI systems
                        • 2. Transparency and explainability
                          Machine Learning Fundamentals- Model evaluation basics
                          • 1. Training vs testing
                            • 2. Basic evaluation metrics
                              - Core ML concepts
                              • 1. Supervised learning
                                • 2. Unsupervised learning
                                  IBM AI Tools and Ecosystem- IBM Watson overview
                                  • 1. AI services and capabilities
                                    • 2. Enterprise AI applications
                                      Natural Language Processing and Computer Vision- Computer vision basics
                                      • 1. Image recognition concepts
                                        • 2. Object detection overview
                                          - NLP basics
                                          • 1. Language understanding tasks
                                            • 2. Text processing concepts

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