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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q53-Q58):

NEW QUESTION # 53
In an AI-powered automation workflow, what is the function of an approval gate?

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

Answer: A

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 # 54
What is hallucination in generative AI?

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

Answer: C

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

NEW QUESTION # 55
A practitioner must reduce the financial cost of a high-volume summarization task. Which strategy addresses token-based billing?

A. increasing the model sampling rate
B. expanding the total context window
C. increasing the model temperature
D. minimizing the input prompt size

Answer: D

Explanation:
Token-based billing is driven by the number of input and output tokens processed, so reducing the prompt size lowers the total tokens consumed across high-volume summarization requests.

NEW QUESTION # 56
Why is a Human-in-the-Loop requirement essential for AI governance in high-stakes environments like healthcare or finance?

A. to protect sensitive customer data
B. to increase the speed of AI response
C. to prevent unauthorized access to data
D. to ensure the validity of AI decisions

Answer: D

Explanation:
Human-in-the-Loop governance ensures that a qualified person reviews, validates, and can override AI-generated decisions when outcomes may significantly affect people, such as medical diagnoses, treatment decisions, credit approvals, or financial risk assessments.

NEW QUESTION # 57
Which software development lifecycle phase utilizes AI to analyze stakeholder documentation for logical inconsistencies and to draft structured user stories?

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

Answer: C

Explanation:
In the requirements phase, AI can analyze stakeholder documentation to identify logical gaps or inconsistencies and help convert business needs into structured user stories.

NEW QUESTION # 58
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