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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Generative AI Models20%- Context and retrieval systems
  • 1. RAG, embeddings, vector databases
    • 2. Context windows and token limits
      - Model hosting and architecture
      • 1. Latency, cost, privacy considerations
        • 2. Cloud vs local deployment trade-offs
          - Model fundamentals and use cases
          • 1. Use cases: summarization, code generation, content creation
            • 2. LLMs and diffusion models overview
              Topic 2: AI for Data Research and Analysis- Data exploration and transformation
              • 1. Insight generation and validation
                • 2. AI-assisted data cleaning
                  Topic 3: Ethics and Security15%- Responsible AI principles
                  • 1. Bias mitigation
                    • 2. Fairness, transparency, accountability
                      - AI security threats
                      • 1. AI-specific attack surfaces
                        • 2. Misinformation and hallucinations
                          - Data privacy and governance
                          • 1. Secure AI data handling
                            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: Agentic AI Systems- Agent architecture
                                      • 1. Autonomous agents and orchestration
                                        • 2. Multi-step reasoning workflows
                                          Topic 6: 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

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                                                  Cisco AI Technical Practitioner Sample Questions (Q31-Q36):

                                                  NEW QUESTION # 31
                                                  In an AI-powered automation workflow, what is deterministic branching?

                                                  Answer: C

                                                  Explanation:
                                                  Deterministic branching uses predefined rules or conditions to decide the next workflow step, making the path predictable and repeatable rather than model-driven or manually selected.


                                                  NEW QUESTION # 32
                                                  Which approach protects PII when utilizing a public AI service for data analysis?

                                                  Answer: D

                                                  Explanation:
                                                  Anonymizing or redacting sensitive personal information before sending data to a public AI service prevents PII from being exposed outside the organization's controlled environment.


                                                  NEW QUESTION # 33
                                                  Why are embeddings essential to the retrieval phase of a RAG system?

                                                  Answer: C

                                                  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 # 34
                                                  Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?

                                                  Answer: D

                                                  Explanation:
                                                  Knowledge cut-off occurs when a model lacks information about events, standards, or specifications released after its training data period, causing it to provide outdated information.


                                                  NEW QUESTION # 35
                                                  A practitioner is using AI to analyze customer support tickets and usage data to compare customer complaint patterns across segments. According to the 4-step EDA methodology, what is the next action after generating a high-level summary of the feedback?

                                                  Answer: C

                                                  Explanation:
                                                  In the 4-step EDA methodology, after orienting with a high-level summary, the next step is to form hypotheses about possible patterns or relationships in the data, such as why complaint patterns differ across customer segments.


                                                  NEW QUESTION # 36
                                                  ......

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