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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI for Code and Workflow Optimization	15%	- Integration of AI tools in development processes - AI-assisted code generation and improvement - Automation and workflow enhancement
Topic 2: Prompt Engineering	15%	- Defensive prompting and error mitigation - Prompt design principles and best practices - Advanced prompting techniques
Topic 3: 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
Topic 4: Generative AI Models	20%	- Context windows, token limits and response management - Model selection and evaluation in AI hubs - Generative AI model families and use cases - Model hosting options and trade-offs
Topic 5: Data Research and Analysis	15%	- Data visualization and insight generation - Data collection, preparation and preprocessing - Data quality, bias and validation
Topic 6: 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

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

NEW QUESTION # 41
What is a difference between generative AI and agentic AI?

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

Answer: A

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 # 42
Which algorithm category is used when no labels exist in data?

A. Supervised learning
B. Unsupervised learning
C. Deterministic routing
D. Reinforcement learning only

Answer: B

Explanation:
Unsupervised learning discovers patterns or groupings without labeled outputs.

NEW QUESTION # 43
In an AI-powered automation workflow, what is deterministic branching?

A. A decision point where the next step is dictated by specific, pre-programmed rules.
B. A process where the AI model autonomously selects the next step based on its internal confidence score.
C. A dynamic system where branching criteria evolve over time using optimization algorithms.
D. A workflow state that pauses execution until a human manually determines the next step.

Answer: A

Explanation:
Deterministic branching uses predefined rules or conditions to decide the next workflow step, making the path predictable and repeatable rather than model-driven or manually selected.

NEW QUESTION # 44
What is the role of the client in the Model Context Protocol?

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

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 # 45
Why is defining a persona considered a best practice for technical prompt engineering?

A. It provides a pattern to emulate.
B. It guides the tone and vocabulary.
C. It reduces the total token usage.
D. It provides instructions for desired action.

Answer: B

Explanation:
Defining a persona guides the AI to respond with the appropriate role-based tone, vocabulary, level of technical depth, and communication style for the intended audience.

NEW QUESTION # 46
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