Most Probable Real Cisco Exam Questions in 810-110 PDF Format

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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
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
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
AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning
Generative AI Models	20%	- Model fundamentals and use cases 1. Use cases: summarization, code generation, content creation 2. LLMs and diffusion models overview - Model hosting and architecture 1. Cloud vs local deployment trade-offs 2. Latency, cost, privacy considerations - Context and retrieval systems 1. RAG, embeddings, vector databases 2. Context windows and token limits
Ethics and Security	15%	- Responsible AI principles 1. Bias mitigation 2. Fairness, transparency, accountability - AI security threats 1. AI-specific attack surfaces 2. Misinformation and hallucinations - Data privacy and governance 1. Secure AI data handling
Agentic AI Systems		- Agent architecture 1. Autonomous agents and orchestration 2. Multi-step reasoning workflows

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Cisco AI Technical Practitioner Sample Questions (Q65-Q70):

NEW QUESTION # 65
A user includes project background information and the specific technical constraints in a prompt.
Which principle of prompt engineering is being applied?

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

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 # 66
What is a purpose of providing a JSON schema when configuring tool use for an AI agent?

A. to map relationships between multiple tools in an agent workflow
B. to define the required parameters and data types the agent must return
C. to reduce the token count of the agent's system prompt
D. to encrypt the payload before it is sent to the external service

Answer: B

Explanation:
A JSON schema defines the structure, required fields, and data types for tool calls, helping the agent provide valid inputs or outputs that the external tool can process reliably.

NEW QUESTION # 67
Which algorithm category is used when no labels exist in data?

A. Deterministic routing
B. Reinforcement learning only
C. Unsupervised learning
D. Supervised learning

Answer: C

Explanation:
Unsupervised learning discovers patterns or groupings without labeled outputs.

NEW QUESTION # 68
Which threat involves an attacker intentionally contaminating the training set of a model to influence its future behavior?

A. direct prompt injection
B. algorithmic bias
C. data poisoning
D. gradient inversion

Answer: C

Explanation:
Data poisoning occurs when an attacker deliberately manipulates or contaminates training data so the model learns harmful, biased, or attacker-controlled behavior.

NEW QUESTION # 69
Which metric is commonly used to evaluate classification models?

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

Answer: A

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

NEW QUESTION # 70
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