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Cisco 810-110 Exam Syllabus Topics:

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

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                                                  Cisco AI Technical Practitioner Sample Questions (Q21-Q26):

                                                  NEW QUESTION # 21
                                                  What is occurring when an agent converts a CSV list into a Markdown table for a final report?

                                                  Answer: A

                                                  Explanation:
                                                  Data transformation changes data from one format or structure into another, such as converting CSV rows into a Markdown table for reporting.


                                                  NEW QUESTION # 22
                                                  A marketing team must generate high-fidelity images for a new product launch. Which model is designed to handle this task through the process of iterative noise reduction?

                                                  Answer: B

                                                  Explanation:
                                                  Diffusion models generate high-fidelity images by starting from noise and iteratively denoising it over multiple steps until a coherent image is produced.


                                                  NEW QUESTION # 23
                                                  Why is a Human-in-the-Loop requirement essential for AI governance in high-stakes environments like healthcare or finance?

                                                  Answer: D

                                                  Explanation:
                                                  Human-in-the-Loop governance ensures that a qualified person reviews, validates, and can override AI-generated decisions when outcomes may significantly affect people, such as medical diagnoses, treatment decisions, credit approvals, or financial risk assessments.


                                                  NEW QUESTION # 24
                                                  What is a corporate data privacy risk when using a public AI chatbot?

                                                  Answer: A

                                                  Explanation:
                                                  A public AI chatbot may retain submitted corporate data or use it to improve model training, which can expose confidential, proprietary, or regulated information outside the organization's control.


                                                  NEW QUESTION # 25
                                                  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: D

                                                  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 # 26
                                                  ......

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