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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Generative AI Models	20%	- Context and retrieval systems 1. Context windows and token limits 2. RAG, embeddings, vector databases - 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. AI-assisted data cleaning 2. Insight generation and validation
Ethics and Security	15%	- Data privacy and governance 1. Secure AI data handling - AI security threats 1. Misinformation and hallucinations 2. AI-specific attack surfaces - Responsible AI principles 1. Fairness, transparency, accountability 2. Bias mitigation
Agentic AI Systems		- Agent architecture 1. Autonomous agents and orchestration 2. Multi-step reasoning workflows
AI for Code and Workflow Optimization		- Automation workflows 1. API integration basics 2. Workflow orchestration concepts - AI-assisted software development 1. Code generation and debugging 2. SDLC integration
Prompt Engineering	15%	- Prompt design principles 1. Roles, instructions, constraints - Prompting techniques 1. Chained and iterative prompting 2. Few-shot prompting - Security and robustness 1. Prompt injection risks 2. Mitigation and defensive prompting

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Cisco AI Technical Practitioner Sample Questions (Q42-Q47):

NEW QUESTION # 42
Which AI concern focuses on protecting sensitive information?

A. VLAN tagging
B. Packet fragmentation
C. Data privacy
D. Clock synchronization

Answer: C

Explanation:
AI systems must ensure sensitive data is securely handled and protected.

NEW QUESTION # 43
Why is a Human-in-the-Loop workflow essential when an AI agent has write access to a production database?

A. to provide administrative credentials required to bypass MFA requirements
B. to allow the AI agent to bypass the integrity constraints of the database
C. to serve as a safety gate against unintended data modifications
D. to allow the AI agent to automatically resolve transaction deadlocks

Answer: C

Explanation:
A Human-in-the-Loop workflow adds human approval before the agent performs high-risk write operations, helping prevent accidental, incorrect, or harmful changes to production data.

NEW QUESTION # 44
Which metric is commonly used to evaluate classification models?

A. Voltage
B. Throughput only
C. Accuracy
D. Packet TTL

Answer: C

Explanation:
Accuracy measures how many predictions were correct out of total predictions.

NEW QUESTION # 45
Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?

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

Answer: B

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 # 46
Which role does AI play in assisting with the refactoring of software code?

A. integrating a new API
B. reducing manual code documentation
C. creating a new database schema
D. identifying flaws and improving design

Answer: D

Explanation:
AI-assisted refactoring helps analyze existing code to identify design flaws, simplify structure, improve readability, and maintain behavior while making the code easier to maintain.

NEW QUESTION # 47
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