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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q45-Q50):

NEW QUESTION # 45
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 # 46
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. providing inline co-pilot assistance
B. implementing predictive function logic
C. executing legacy code refactoring
D. performing code scaffolding

Answer: D

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 # 47
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 # 48
What is the benefit of AI Ops (AIOps) in networking?

A. Eliminates all routers
B. Disables telemetry
C. Removes cloud computing
D. Automates monitoring and incident analysis

Answer: D

Explanation:
AIOps uses AI to improve IT operations, detect anomalies, and accelerate troubleshooting.

NEW QUESTION # 49
Which AI-driven activity involves a developer providing runtime error logs to a model to receive an explanation of the root cause and a suggested fix?

A. continuous integration optimization
B. AI-assisted debugging
C. automated unit testing
D. code scaffolding

Answer: B

Explanation:
AI-assisted debugging uses error logs, stack traces, and runtime context to help identify the root cause of a failure and suggest a corrective fix.

NEW QUESTION # 50
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