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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
AI for Code and Workflow Optimization15%- Automation and workflow enhancement
- AI-assisted code generation and improvement
- Integration of AI tools in development processes
Generative AI Models20%- Model hosting options and trade-offs
- Context windows, token limits and response management
- Generative AI model families and use cases
- Model selection and evaluation in AI hubs
Data Research and Analysis15%- Data visualization and insight generation
- Data quality, bias and validation
- Data collection, preparation and preprocessing
Agentic AI15%- Human-in-the-loop strategies
- Agent design principles and capabilities
- Model Context Protocol (MCP) framework
- Agentic AI vs Generative AI use cases
AI Ethics and Security20%- AI-specific threats, risks and misinformation
- Data privacy and security in AI systems
- Responsible AI principles
- Compliance and governance frameworks
Prompt Engineering15%- Prompt design principles and best practices
- Advanced prompting techniques
- Defensive prompting and error mitigation

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Cisco AI Technical Practitioner Sample Questions (Q30-Q35):

NEW QUESTION # 30
What is the role of embeddings in AI systems?

Answer: A

Explanation:
Embeddings convert text or objects into vectors that capture semantic meaning.


NEW QUESTION # 31
What is a purpose of providing a JSON schema when configuring tool use for an AI agent?

Answer: C

Explanation:
A JSON schema defines the structure, required fields, and data types for tool calls, helping the agent provide valid inputs or outputs that the external tool can process reliably.


NEW QUESTION # 32
Why is a Human-in-the-Loop workflow essential when an AI agent has write access to a production database?

Answer: B

Explanation:
A Human-in-the-Loop workflow adds human approval before the agent performs high-risk write operations, helping prevent accidental, incorrect, or harmful changes to production data.


NEW QUESTION # 33
Which Cisco AI capability helps detect abnormal network behavior?

Answer: B

Explanation:
AI systems can identify unusual patterns and potential threats automatically.


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Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?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

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
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