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Cisco 810-110 Exam Syllabus Topics:

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

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                                                  Cisco AI Technical Practitioner Sample Questions (Q39-Q44):

                                                  NEW QUESTION # 39
                                                  When using AI to draft a technical proposal, what is the benefit of a format-agnostic strategy?

                                                  Answer: C

                                                  Explanation:
                                                  A format-agnostic strategy keeps the content independent of a specific final layout, making it easier to reuse or adapt the same proposal material for different formats such as email, slides, documents, or reports.


                                                  NEW QUESTION # 40
                                                  What is the purpose of tokenization in Large Language Models (LLMs)?

                                                  Answer: B

                                                  Explanation:
                                                  Tokenization converts text into smaller units (tokens) that AI models can process.


                                                  NEW QUESTION # 41
                                                  Why are embeddings essential to the retrieval phase of a RAG system?

                                                  Answer: D

                                                  Explanation:
                                                  Embeddings convert text into numerical vectors that capture semantic meaning, allowing a RAG system to retrieve content that is conceptually relevant to the user's query rather than relying only on exact keyword matches.


                                                  NEW QUESTION # 42
                                                  What is the primary goal of Retrieval-Augmented Generation (RAG) in AI systems?

                                                  Answer: D

                                                  Explanation:
                                                  RAG combines a large language model with external data retrieval systems so the model can answer using updated and domain-specific knowledge.


                                                  NEW QUESTION # 43
                                                  Which Cisco platform provides AI-powered security analytics?

                                                  Answer: B

                                                  Explanation:
                                                  Cisco SecureX integrates security visibility, analytics, and automation using AI-driven insights.


                                                  NEW QUESTION # 44
                                                  ......

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