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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q72-Q77):

NEW QUESTION # 72
A team uses AI to scaffold a new microservice. What does this process involve?

A. removing redundant logic
B. testing the final production code
C. generating the initial structure
D. creating automated deployment scripts

Answer: C

Explanation:
Scaffolding uses AI to generate the initial project structure, boilerplate files, configuration, and basic code layout so the team can start development faster.

NEW QUESTION # 73
A practitioner uses self-consistency by running the same prompt three times and comparing the results. What is the goal of this strategy?

A. to bypass the context window
B. to increase the model creativity
C. to increase the response speed
D. to verify the output reliability

Answer: D

Explanation:
Self-consistency compares multiple responses to the same prompt to check whether the model produces stable, reliable results across repeated runs.

NEW QUESTION # 74
What is hallucination in generative AI?

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

Answer: B

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

NEW QUESTION # 75
Which approach protects PII when utilizing a public AI service for data analysis?

A. utilizing system prompts to instruct the AI to ignore sensitive data fields
B. ensuring the AI provider maintains industry-standard SOC 2 compliance
C. anonymizing or redacting PH from the dataset before transmitting the request
D. encrypting the data payload during transit to the AI service provider

Answer: C

Explanation:
Anonymizing or redacting sensitive personal information before sending data to a public AI service prevents PII from being exposed outside the organization's controlled environment.

NEW QUESTION # 76
Which factor should be considered when selecting a pre-trained model for a mobile application with limited local computational resources?

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

Answer: C

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 # 77
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