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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q47-Q52):

NEW QUESTION # 47
A practitioner is solving a complex architectural problem by breaking it into four sequential prompts. Each prompt's output is fed as input into the next prompt in the sequence. Which prompt engineering technique is being used?

A. meta-prompting
B. prompt chaining
C. few-shot prompting
D. chain-of-thought prompting

Answer: B

Explanation:
Prompt chaining breaks a complex task into a sequence of connected prompts, where each response becomes part of the input for the next step.

NEW QUESTION # 48
Which AI-driven activity involves a developer providing runtime error logs to a model to receive an explanation of the root cause and a suggested fix?

A. automated unit testing
B. code scaffolding
C. AI-assisted debugging
D. continuous integration optimization

Answer: C

Explanation:
AI-assisted debugging uses error logs, stack traces, and runtime context to help identify the root cause of a failure and suggest a corrective fix.

NEW QUESTION # 49
Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?

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

Answer: A

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 # 50
Which Cisco platform provides AI-powered security analytics?

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

Answer: A

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

NEW QUESTION # 51
What is a use case for generative AI in the testing phase of the software development lifecycle?

A. drafting user stories
B. performing static code analysis
C. generating synthetic test data
D. generating automated documentation

Answer: C

Explanation:
Generative AI can create synthetic test data that simulates realistic inputs and edge cases, helping validate application behavior during the testing phase without relying only on production data.

NEW QUESTION # 52
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