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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q41-Q46):

NEW QUESTION # 41
Which activity occurs when a developer uses AI to generate a complete Python class for a new API client based on a high-level description?

A. implementing predictive function logic
B. performing code scaffolding
C. providing inline co-pilot assistance
D. executing legacy code refactoring

Answer: B

Explanation:
Code scaffolding uses AI to generate the initial structure and boilerplate for a new component, such as a complete Python class for an API client based on a high-level description.

NEW QUESTION # 42
What is a difference between generative AI and agentic AI?

A. Generative AI operates autonomously and agentic AI requires a prompt for each action.
B. Generative AI produces single-turn responses and agentic AI executes multi-step reasoning loops.
C. Generative AI requires tool access and agentic AI relies on its training data.
D. Generative AI uses retrieval-augmented generation and agentic AI does not support external data sources.

Answer: B

Explanation:
Generative AI primarily creates content or responses from a prompt, while agentic AI can plan, reason, use tools, and execute multi-step workflows toward a goal.

NEW QUESTION # 43
Which AI model type is best suited for image recognition tasks?

A. Decision Tree only
B. Convolutional Neural Network (CNN)
C. Linear Regression
D. K-Means

Answer: B

Explanation:
CNNs are optimized for image and visual pattern recognition.

NEW QUESTION # 44
What is hallucination in generative AI?

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

Answer: A

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

NEW QUESTION # 45
A practitioner is using AI to analyze customer support tickets and usage data to compare customer complaint patterns across segments. According to the 4-step EDA methodology, what is the next action after generating a high-level summary of the feedback?

A. hypothesize
B. correlate
C. visualize
D. orient

Answer: A

Explanation:
In the 4-step EDA methodology, after orienting with a high-level summary, the next step is to form hypotheses about possible patterns or relationships in the data, such as why complaint patterns differ across customer segments.

NEW QUESTION # 46
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