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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Agentic AI Systems		- Agent architecture 1. Multi-step reasoning workflows 2. Autonomous agents and orchestration
AI for Code and Workflow Optimization		- Automation workflows 1. Workflow orchestration concepts 2. API integration basics - AI-assisted software development 1. SDLC integration 2. Code generation and debugging
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
Ethics and Security	15%	- Responsible AI principles 1. Bias mitigation 2. Fairness, transparency, accountability - Data privacy and governance 1. Secure AI data handling - AI security threats 1. AI-specific attack surfaces 2. Misinformation and hallucinations
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. Mitigation and defensive prompting 2. Prompt injection risks
AI for Data Research and Analysis		- Data exploration and transformation 1. AI-assisted data cleaning 2. Insight generation and validation

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Cisco AI Technical Practitioner Sample Questions (Q36-Q41):

NEW QUESTION # 36
How does AI support exploratory data analysis when working with large, unstructured datasets?

A. by performing bit-by-bit reconstruction
B. by compressing the datasets
C. by tuning inference parameters
D. by identifying patterns and groupings

Answer: D

Explanation:
AI supports exploratory data analysis by detecting patterns, clusters, themes, and relationships in large unstructured datasets, helping practitioners understand the data before deeper analysis.

NEW QUESTION # 37
A company discloses to its users that their support tickets are being summarized by an AI model.
Which responsible AI principle does this action support?

A. bias mitigation
B. transparency
C. inclusiveness
D. system safety

Answer: B

Explanation:
Transparency means clearly informing users when AI is being used, what it is doing, and how it may affect their data or experience.

NEW QUESTION # 38
Which Cisco AI capability helps detect abnormal network behavior?

A. Manual packet counting
B. Static routing
C. AI-driven anomaly detection
D. BIOS recovery mode

Answer: C

Explanation:
AI systems can identify unusual patterns and potential threats automatically.

NEW QUESTION # 39
What is the role of embeddings in AI systems?

A. Representing data numerically in vector space
B. Encrypting traffic
C. Compressing logs
D. Assigning IP addresses

Answer: A

Explanation:
Embeddings convert text or objects into vectors that capture semantic meaning.

NEW QUESTION # 40
Which strategy should be used to mitigate hallucinations when asking an AI to summarize a specific technical document?

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

Answer: A

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 # 41
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