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IBM S2000-027 Exam Syllabus Topics:

SectionObjectives
Deep Learning and Neural Networks- Neural network concepts
  • 1. Training and optimization concepts
    • 2. Perceptron and layers
      Machine Learning Fundamentals- Core ML approaches
      • 1. Reinforcement learning overview
        • 2. Unsupervised learning basics
          • 3. Supervised learning basics
            AI Applications and Use Cases- Industry applications
            • 1. Computer vision applications
              • 2. AI in business and automation
                • 3. Natural language processing applications
                  Ethics and Responsible AI- Responsible AI principles
                  • 1. Transparency and explainability
                    • 2. Bias and fairness considerations
                      Introduction to Artificial Intelligence- Fundamental AI concepts and terminology
                      • 1. Types of AI systems (narrow vs general AI)
                        • 2. Definition of AI, ML, and DL

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