Cisco AI Technical Practitioner : 810-110

  • Exam Code: 810-110
  • Exam Name: Cisco AI Technical Practitioner
  • Updated: Aug 21, 2026
  • Q & A: 73 Questions and Answers

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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Generative AI Models20%- Model hosting strategies
  • 1. Cost, latency, privacy, and scalability considerations
  • 2. Cloud-based vs. local deployments
- Context windows and token management
  • 1. Response management
  • 2. Token limits
- Major generative model families
  • 1. Diffusion models
  • 2. Large language models (LLMs)
- Common use cases
  • 1. Content creation
  • 2. Text summarization
  • 3. Code generation
- Model selection
  • 1. Reasoning and multimodal tasks
  • 2. Selection from AI hubs
- Retrieval Augmented Generation (RAG)
  • 1. Vector databases
  • 2. Embeddings
  • 3. Grounding AI outputs in external knowledge
Topic 2: AI Ethics and Security- Security threats and mitigations
  • 1. Model security
  • 2. Data privacy
- Ethical considerations in AI
  • 1. Transparency and explainability
  • 2. Bias and fairness
Topic 3: Prompt Engineering15%- Prompt structures
  • 1. Text generation
  • 2. Image generation
  • 3. Audio generation
- Principles and patterns
  • 1. Constraints
  • 2. Roles
  • 3. Instructions
- Prompting techniques
  • 1. Iterative prompting
  • 2. Few-shot prompting
  • 3. Chained prompting
- Security and safety
  • 1. Reducing hallucinations
  • 2. Defensive prompting methods
  • 3. Improving response accuracy
  • 4. Prompt injection attacks
Topic 4: Data Research and Analysis- Data collection and preparation
  • 1. Data cleaning and preprocessing
  • 2. Data gathering methodologies
- Data analysis techniques
  • 1. Data visualization
  • 2. Statistical analysis
Topic 5: Agentic AI20%- Model Context Protocol (MCP)
  • 1. MCP framework primitives
  • 2. Context in agentic AI
- Differentiation from Generative AI
  • 1. Autonomous capabilities
  • 2. Use cases comparison
- AI agent design principles
  • 1. Orchestration
  • 2. Human-in-the-loop (HITL) strategies
- Data transformation and mapping
  • 1. Within AI Agents
Topic 6: AI for Code and Workflow Optimization- AI-assisted code development
  • 1. Code review and debugging
  • 2. Code generation
- Workflow automation
  • 1. Task optimization
  • 2. Process automation

Cisco AI Technical Practitioner Sample Questions:

1. What is a difference between generative AI and agentic AI?

A) Generative AI operates autonomously and agentic AI requires a prompt for each action.
B) Generative AI requires tool access and agentic AI relies on its training data.
C) Generative AI uses retrieval-augmented generation and agentic AI does not support external data sources.
D) Generative AI produces single-turn responses and agentic AI executes multi-step reasoning loops.


2. What is the role of embeddings in AI systems?

A) Representing data numerically in vector space
B) Compressing logs
C) Encrypting traffic
D) Assigning IP addresses


3. Which Cisco AI capability helps detect abnormal network behavior?

A) BIOS recovery mode
B) Manual packet counting
C) AI-driven anomaly detection
D) Static routing


4. A practitioner is estimating the operational cost of integrating a cloud-hosted LLM API into an application. How does tokenization influence the cost of using this API?

A) Costs are determined by the number of API calls.
B) Tokenization has no impact because pricing is based on a flat-rate subscription.
C) Tokenization increases cost by requiring additional GPU run time.
D) The number of tokens determines the per-request cost.


5. Which software development lifecycle phase utilizes AI to analyze stakeholder documentation for logical inconsistencies and to draft structured user stories?

A) requirements
B) testing
C) implementation
D) maintenance


Solutions:

Question # 1
Answer: D
Question # 2
Answer: A
Question # 3
Answer: C
Question # 4
Answer: D
Question # 5
Answer: A

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