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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Generative AI Models20%- Model hosting and architecture
  • 1. Latency, cost, privacy considerations
    • 2. Cloud vs local deployment trade-offs
      - Model fundamentals and use cases
      • 1. LLMs and diffusion models overview
        • 2. Use cases: summarization, code generation, content creation
          - Context and retrieval systems
          • 1. RAG, embeddings, vector databases
            • 2. Context windows and token limits
              Topic 2: Ethics and Security15%- Data privacy and governance
              • 1. Secure AI data handling
                - AI security threats
                • 1. AI-specific attack surfaces
                  • 2. Misinformation and hallucinations
                    - Responsible AI principles
                    • 1. Bias mitigation
                      • 2. Fairness, transparency, accountability
                        Topic 3: Agentic AI Systems- Agent architecture
                        • 1. Multi-step reasoning workflows
                          • 2. Autonomous agents and orchestration
                            Topic 4: Prompt Engineering15%- Security and robustness
                            • 1. Prompt injection risks
                              • 2. Mitigation and defensive prompting
                                - Prompting techniques
                                • 1. Chained and iterative prompting
                                  • 2. Few-shot prompting
                                    - Prompt design principles
                                    • 1. Roles, instructions, constraints
                                      Topic 5: AI for Code and Workflow Optimization- Automation workflows
                                      • 1. Workflow orchestration concepts
                                        • 2. API integration basics
                                          - AI-assisted software development
                                          • 1. SDLC integration
                                            • 2. Code generation and debugging
                                              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 (Q33-Q38):

                                                  NEW QUESTION # 33
                                                  Which concept helps reduce overfitting in machine learning?

                                                  Answer: D

                                                  Explanation:
                                                  Regularization techniques help models generalize better and avoid memorizing training data.


                                                  NEW QUESTION # 34
                                                  A team uses AI to scaffold a new microservice. What does this process involve?

                                                  Answer: C

                                                  Explanation:
                                                  Scaffolding uses AI to generate the initial project structure, boilerplate files, configuration, and basic code layout so the team can start development faster.


                                                  NEW QUESTION # 35
                                                  Which strategy should be used to mitigate hallucinations when asking an AI to summarize a specific technical document?

                                                  Answer: C

                                                  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 # 36
                                                  What is hallucination in generative AI?

                                                  Answer: D

                                                  Explanation:
                                                  Hallucination occurs when an AI confidently produces false or misleading outputs.


                                                  NEW QUESTION # 37
                                                  Which algorithm category is used when no labels exist in data?

                                                  Answer: C

                                                  Explanation:
                                                  Unsupervised learning discovers patterns or groupings without labeled outputs.


                                                  NEW QUESTION # 38
                                                  ......

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