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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q17-Q22):

NEW QUESTION # 17
A user includes project background information and the specific technical constraints in a prompt.
Which principle of prompt engineering is being applied?

A. stating the purpose
B. describing the situation
C. defining a persona
D. using few-shot

Answer: B

Explanation:
Describing the situation means providing relevant context, background information, and constraints so the AI can generate a response that fits the specific scenario.

NEW QUESTION # 18
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 provide the GUI for the end-user interaction
C. to route requests between different AI providers
D. to host the LLM and perform token inference

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 # 19
Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?

A. misinformation
B. data poisoning
C. disinformation
D. knowledge cut-off

Answer: D

Explanation:
Knowledge cut-off occurs when a model lacks information about events, standards, or specifications released after its training data period, causing it to provide outdated information.

NEW QUESTION # 20
What is the benefit of AI Ops (AIOps) in networking?

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

Answer: C

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

NEW QUESTION # 21
Why is a Human-in-the-Loop requirement essential for AI governance in high-stakes environments like healthcare or finance?

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

Answer: A

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 # 22
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