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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Generative AI Models	20%	- Context and retrieval systems 1. RAG, embeddings, vector databases 2. Context windows and token limits - Model hosting and architecture 1. Cloud vs local deployment trade-offs 2. Latency, cost, privacy considerations - Model fundamentals and use cases 1. Use cases: summarization, code generation, content creation 2. LLMs and diffusion models overview
AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning
Ethics and Security	15%	- Data privacy and governance 1. Secure AI data handling - Responsible AI principles 1. Fairness, transparency, accountability 2. Bias mitigation - AI security threats 1. Misinformation and hallucinations 2. AI-specific attack surfaces
Agentic AI Systems		- Agent architecture 1. Multi-step reasoning workflows 2. Autonomous agents and orchestration
AI for Code and Workflow Optimization		- Automation workflows 1. API integration basics 2. Workflow orchestration concepts - AI-assisted software development 1. SDLC integration 2. Code generation and debugging
Prompt Engineering	15%	- Security and robustness 1. Mitigation and defensive prompting 2. Prompt injection risks - Prompt design principles 1. Roles, instructions, constraints - Prompting techniques 1. Few-shot prompting 2. Chained and iterative prompting

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Cisco AI Technical Practitioner Sample Questions (Q35-Q40):

NEW QUESTION # 35
A practitioner must reduce the financial cost of a high-volume summarization task. Which strategy addresses token-based billing?

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

Answer: B

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 # 36
Which Cisco platform provides AI-powered security analytics?

A. Cisco Packet Tracer
B. Cisco IOS ROMMON
C. Cisco UCS Manager only
D. Cisco SecureX

Answer: D

Explanation:
Cisco SecureX integrates security visibility, analytics, and automation using AI-driven insights.

NEW QUESTION # 37
Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?

A. using smaller contexts
B. implementing constraints
C. removing system prompts
D. using known patterns

Answer: B

Explanation:
Implementing constraints, such as maximum iteration limits, stop conditions, and execution boundaries, helps prevent an autonomous agent from repeatedly running actions without reaching a valid endpoint.

NEW QUESTION # 38
Which activity is an agentic AI use case compared to a standard generative AI use case?

A. generating a meeting summary
B. autonomously fixing a build
C. writing a poem about routing
D. translating a short email

Answer: B

Explanation:
Agentic AI can plan and execute multi-step actions toward a goal, such as diagnosing a failed build, applying a fix, running validation, and iterating until the build succeeds.

NEW QUESTION # 39
What is the role of an MCP server in the MCP open standard?

A. to expose tools and resources to an AI model
B. to route requests between different AI providers
C. to host the LLM and perform token inference
D. to provide the GUI for the end-user interaction

Answer: A

Explanation:
An MCP server exposes external tools, data sources, and resources through a standardized interface so an AI model or agent can access capabilities beyond its built-in training data.

NEW QUESTION # 40
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