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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Ethics and Security15%- AI security threats
  • 1. AI-specific attack surfaces
    • 2. Misinformation and hallucinations
      - Data privacy and governance
      • 1. Secure AI data handling
        - Responsible AI principles
        • 1. Bias mitigation
          • 2. Fairness, transparency, accountability
            Topic 2: AI for Code and Workflow Optimization- AI-assisted software development
            • 1. SDLC integration
              • 2. Code generation and debugging
                - Automation workflows
                • 1. Workflow orchestration concepts
                  • 2. API integration basics
                    Topic 3: Agentic AI Systems- Agent architecture
                    • 1. Multi-step reasoning workflows
                      • 2. Autonomous agents and orchestration
                        Topic 4: Generative AI Models20%- Context and retrieval systems
                        • 1. RAG, embeddings, vector databases
                          • 2. Context windows and token limits
                            - Model fundamentals and use cases
                            • 1. LLMs and diffusion models overview
                              • 2. Use cases: summarization, code generation, content creation
                                - Model hosting and architecture
                                • 1. Latency, cost, privacy considerations
                                  • 2. Cloud vs local deployment trade-offs
                                    Topic 5: Prompt Engineering15%- Prompting techniques
                                    • 1. Chained and iterative prompting
                                      • 2. Few-shot prompting
                                        - Security and robustness
                                        • 1. Prompt injection risks
                                          • 2. Mitigation and defensive prompting
                                            - Prompt design principles
                                            • 1. Roles, instructions, constraints
                                              Topic 6: AI for Data Research and Analysis- Data exploration and transformation
                                              • 1. Insight generation and validation
                                                • 2. AI-assisted data cleaning

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                                                  Cisco AI Technical Practitioner Sample Questions (Q58-Q63):

                                                  NEW QUESTION # 58
                                                  In supervised machine learning, what is required?

                                                  Answer: B


                                                  NEW QUESTION # 59
                                                  Which AI-assisted task standardizes inconsistent date formats (e.g., MM/DD/YY and DD-MM- YYYY)?

                                                  Answer: A

                                                  Explanation:
                                                  Data transformation converts inconsistent data into a consistent format, such as standardizing multiple date formats into one required representation.


                                                  NEW QUESTION # 60
                                                  Which strategy should be used to mitigate hallucinations when asking an AI to summarize a specific technical document?

                                                  Answer: D

                                                  Explanation:
                                                  Requesting citations grounds the summary in the provided technical document and makes the model support its claims with specific source references, reducing the chance of unsupported or fabricated content.


                                                  NEW QUESTION # 61
                                                  Which activity is an agentic AI use case compared to a standard generative AI use case?

                                                  Answer: B

                                                  Explanation:
                                                  Agentic AI can plan and execute multi-step actions toward a goal, such as diagnosing a failed build, applying a fix, running validation, and iterating until the build succeeds.


                                                  NEW QUESTION # 62
                                                  What is an advantage of cloud-hosted API services when comparing cloud-hosted and locally hosted AI models?

                                                  Answer: C

                                                  Explanation:
                                                  Cloud-hosted API services can scale inference capacity quickly based on demand, making them suitable for workloads with unpredictable or fluctuating usage.


                                                  NEW QUESTION # 63
                                                  ......

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