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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Generative AI Models	20%	- Context windows, token limits and response management - Generative AI model families and use cases - Model hosting options and trade-offs - Model selection and evaluation in AI hubs
Topic 2: Prompt Engineering	15%	- Defensive prompting and error mitigation - Advanced prompting techniques - Prompt design principles and best practices
Topic 3: AI Ethics and Security	20%	- Compliance and governance frameworks - Data privacy and security in AI systems - AI-specific threats, risks and misinformation - Responsible AI principles
Topic 4: Data Research and Analysis	15%	- Data visualization and insight generation - Data quality, bias and validation - Data collection, preparation and preprocessing
Topic 5: AI for Code and Workflow Optimization	15%	- Integration of AI tools in development processes - AI-assisted code generation and improvement - Automation and workflow enhancement
Topic 6: Agentic AI	15%	- Agent design principles and capabilities - Model Context Protocol (MCP) framework - Agentic AI vs Generative AI use cases - Human-in-the-loop strategies

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Cisco AI Technical Practitioner Sample Questions (Q18-Q23):

NEW QUESTION # 18
Which strategy should be used to mitigate hallucinations when asking an AI to summarize a specific technical document?

A. using a short system prompt
B. increasing the model creativity
C. requesting citations for the summary
D. removing negative constraints

Answer: C

Explanation:
Requesting citations grounds the summary in the provided technical document and makes the model support its claims with specific source references, reducing the chance of unsupported or fabricated content.

NEW QUESTION # 19
Which factor should be considered when selecting a pre-trained model for a mobile application with limited local computational resources?

A. release frequency of the model
B. training duration of the model
C. response creativity level of the model
D. parameter count of the model

Answer: D

Explanation:
Parameter count affects model size, memory usage, and compute requirements, so a smaller model is usually more suitable for a mobile application with limited local resources.

NEW QUESTION # 20
What is hallucination in generative AI?

A. Network congestion
B. AI generating incorrect or fabricated information
C. GPU overheating
D. Database replication

Answer: B

Explanation:
Hallucination occurs when an AI confidently produces false or misleading outputs.

NEW QUESTION # 21
What is a purpose of providing a JSON schema when configuring tool use for an AI agent?

A. to encrypt the payload before it is sent to the external service
B. to map relationships between multiple tools in an agent workflow
C. to define the required parameters and data types the agent must return
D. to reduce the token count of the agent's system prompt

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 # 22
Which AI concern focuses on protecting sensitive information?

A. Packet fragmentation
B. VLAN tagging
C. Clock synchronization
D. Data privacy

Answer: D

Explanation:
AI systems must ensure sensitive data is securely handled and protected.

NEW QUESTION # 23
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