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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Prompt Engineering	15%	- Advanced prompting techniques - Prompt design principles and best practices - Defensive prompting and error mitigation
AI Ethics and Security	20%	- Data privacy and security in AI systems - Compliance and governance frameworks - Responsible AI principles - AI-specific threats, risks and misinformation
Generative AI Models	20%	- 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 Analysis	15%	- Data quality, bias and validation - Data collection, preparation and preprocessing - Data visualization and insight generation
AI for Code and Workflow Optimization	15%	- Automation and workflow enhancement - Integration of AI tools in development processes - AI-assisted code generation and improvement
Agentic AI	15%	- Agent design principles and capabilities - Agentic AI vs Generative AI use cases - Model Context Protocol (MCP) framework - Human-in-the-loop strategies

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Cisco AI Technical Practitioner Sample Questions (Q67-Q72):

NEW QUESTION # 67
What is hallucination in generative AI?

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

Answer: C

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

NEW QUESTION # 68
What is aggregation bias in the context of AI-assisted data analysis?

A. when data is omitted due to incompatible formats
B. when a summary masks subpatterns
C. when AI fails to combine conflicting patterns
D. when AI uses summary statistics instead of raw data

Answer: B

Explanation:
Aggregation bias occurs when summarized or combined data hides meaningful differences across subgroups, causing important subpatterns to be missed.

NEW QUESTION # 69
Which activity is an agentic AI use case compared to a standard generative AI use case?

A. generating a meeting summary
B. autonomously fixing a build
C. translating a short email
D. writing a poem about routing

Answer: B

Explanation:
Agentic AI can plan and execute multi-step actions toward a goal, such as diagnosing a failed build, applying a fix, running validation, and iterating until the build succeeds.

NEW QUESTION # 70
What is the role of the client in the Model Context Protocol?

A. to act as a tool or service provider
B. to orchestrate interactions with servers
C. to provide resources for task execution
D. to act as an LLM for inferencing

Answer: B

Explanation:
In the Model Context Protocol, the client manages communication between the AI application and MCP servers, coordinating requests for tools, resources, and context needed during task execution.

NEW QUESTION # 71
In an AI-powered automation workflow, what is the function of an approval gate?

A. to ensure the internal logic of AI remains closed for modification
B. to automatically block deployments if system health alerts are active
C. to trigger automated completion notifications to project stakeholders
D. to apply human judgement before high-impact actions are executed

Answer: D

Explanation:
An approval gate adds human review before an automated workflow performs a high-impact action, helping ensure that AI-driven decisions are checked for correctness, risk, and business impact before execution.

NEW QUESTION # 72
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