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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Generative AI Models	20%	- Context and retrieval systems 1. RAG, embeddings, vector databases 2. Context windows and token limits - Model hosting and architecture 1. Latency, cost, privacy considerations 2. Cloud vs local deployment trade-offs - Model fundamentals and use cases 1. Use cases: summarization, code generation, content creation 2. LLMs and diffusion models overview
Topic 2: Agentic AI Systems		- Agent architecture 1. Multi-step reasoning workflows 2. Autonomous agents and orchestration
Topic 3: Prompt Engineering	15%	- Security and robustness 1. Mitigation and defensive prompting 2. Prompt injection risks - Prompting techniques 1. Few-shot prompting 2. Chained and iterative prompting - Prompt design principles 1. Roles, instructions, constraints
Topic 4: 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
Topic 5: AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning
Topic 6: AI for Code and Workflow Optimization		- Automation workflows 1. Workflow orchestration concepts 2. API integration basics - AI-assisted software development 1. Code generation and debugging 2. SDLC integration

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Cisco AI Technical Practitioner Sample Questions (Q34-Q39):

NEW QUESTION # 34
Why is a Human-in-the-Loop requirement essential for AI governance in high-stakes environments like healthcare or finance?

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

Answer: D

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 # 35
An analyst needs a model that can analyze a network topology diagram and a set of configuration logs simultaneously. Which type of model should be selected?

A. diffusion model
B. generative adversarial network
C. embedding model
D. multimodal model

Answer: D

Explanation:
A multimodal model can process and reason over different input types at the same time, such as images from a network topology diagram and text from configuration logs.

NEW QUESTION # 36
Which strategy should be used to mitigate hallucinations when asking an AI to summarize a specific technical document?

A. removing negative constraints
B. increasing the model creativity
C. using a short system prompt
D. requesting citations for the summary

Answer: D

Explanation:
Requesting citations grounds the summary in the provided technical document and makes the model support its claims with specific source references, reducing the chance of unsupported or fabricated content.

NEW QUESTION # 37
What is the role of the client in the Model Context Protocol?

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

Answer: B

NEW QUESTION # 38
What is hallucination in generative AI?

A. GPU overheating
B. Network congestion
C. Database replication
D. AI generating incorrect or fabricated information

Answer: D

Explanation:
Hallucination occurs when an AI confidently produces false or misleading outputs.

NEW QUESTION # 39
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