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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Agentic AI Systems- Agent architecture
  • 1. Autonomous agents and orchestration
    • 2. Multi-step reasoning workflows
      Prompt Engineering15%- Prompting techniques
      • 1. Chained and iterative prompting
        • 2. Few-shot prompting
          - Security and robustness
          • 1. Mitigation and defensive prompting
            • 2. Prompt injection risks
              - Prompt design principles
              • 1. Roles, instructions, constraints
                Generative AI Models20%- Model fundamentals and use cases
                • 1. Use cases: summarization, code generation, content creation
                  • 2. LLMs and diffusion models overview
                    - Model hosting and architecture
                    • 1. Cloud vs local deployment trade-offs
                      • 2. Latency, cost, privacy considerations
                        - Context and retrieval systems
                        • 1. RAG, embeddings, vector databases
                          • 2. Context windows and token limits
                            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
                                    AI for Data Research and Analysis- Data exploration and transformation
                                    • 1. Insight generation and validation
                                      • 2. AI-assisted data cleaning
                                        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. Misinformation and hallucinations
                                                • 2. AI-specific attack surfaces

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                                                  Cisco AI Technical Practitioner Sample Questions (Q22-Q27):

                                                  NEW QUESTION # 22
                                                  Which algorithm category is used when no labels exist in data?

                                                  Answer: A

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


                                                  NEW QUESTION # 23
                                                  What is occurring when an agent converts a CSV list into a Markdown table for a final report?

                                                  Answer: D

                                                  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 # 24
                                                  A practitioner must reduce the financial cost of a high-volume summarization task. Which strategy addresses token-based billing?

                                                  Answer: C

                                                  Explanation:
                                                  Token-based billing is driven by the number of input and output tokens processed, so reducing the prompt size lowers the total tokens consumed across high-volume summarization requests.


                                                  NEW QUESTION # 25
                                                  In supervised machine learning, what is required?

                                                  Answer: A

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


                                                  NEW QUESTION # 26
                                                  Which AI-driven activity involves a developer providing runtime error logs to a model to receive an explanation of the root cause and a suggested fix?

                                                  Answer: B

                                                  Explanation:
                                                  AI-assisted debugging uses error logs, stack traces, and runtime context to help identify the root cause of a failure and suggest a corrective fix.


                                                  NEW QUESTION # 27
                                                  ......

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