Test 810-110 Prep | 810-110 Latest Exam Registration

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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI for Code and Workflow Optimization- Automation workflows
  • 1. API integration basics
    • 2. Workflow orchestration concepts
      - AI-assisted software development
      • 1. SDLC integration
        • 2. Code generation and debugging
          Topic 2: Agentic AI Systems- Agent architecture
          • 1. Autonomous agents and orchestration
            • 2. Multi-step reasoning workflows
              Topic 3: Generative AI Models20%- 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
                      - Context and retrieval systems
                      • 1. RAG, embeddings, vector databases
                        • 2. Context windows and token limits
                          Topic 4: Prompt Engineering15%- Security and robustness
                          • 1. Mitigation and defensive prompting
                            • 2. Prompt injection risks
                              - Prompt design principles
                              • 1. Roles, instructions, constraints
                                - Prompting techniques
                                • 1. Few-shot prompting
                                  • 2. Chained and iterative prompting
                                    Topic 5: Ethics and Security15%- Responsible AI principles
                                    • 1. Fairness, transparency, accountability
                                      • 2. Bias mitigation
                                        - Data privacy and governance
                                        • 1. Secure AI data handling
                                          - AI security threats
                                          • 1. AI-specific attack surfaces
                                            • 2. Misinformation and hallucinations
                                              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 (Q34-Q39):

                                                  NEW QUESTION # 34
                                                  In supervised machine learning, what is required?

                                                  Answer: C

                                                  Explanation:
                                                  Supervised learning trains models using labeled input-output pairs.


                                                  NEW QUESTION # 35
                                                  What is fine-tuning in generative AI?

                                                  Answer: D

                                                  Explanation:
                                                  Fine-tuning adapts a general AI model to specific domains or business use cases.


                                                  NEW QUESTION # 36
                                                  Which software development lifecycle phase utilizes AI to analyze stakeholder documentation for logical inconsistencies and to draft structured user stories?

                                                  Answer: D

                                                  Explanation:
                                                  In the requirements phase, AI can analyze stakeholder documentation to identify logical gaps or inconsistencies and help convert business needs into structured user stories.


                                                  NEW QUESTION # 37
                                                  In supervised machine learning, what is required?

                                                  Answer: C


                                                  NEW QUESTION # 38
                                                  What is a use case for generative AI in the testing phase of the software development lifecycle?

                                                  Answer: D

                                                  Explanation:
                                                  Generative AI can create synthetic test data that simulates realistic inputs and edge cases, helping validate application behavior during the testing phase without relying only on production data.


                                                  NEW QUESTION # 39
                                                  ......

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