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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. 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
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
Prompt Engineering	15%	- Prompting techniques 1. Few-shot prompting 2. Chained and iterative prompting - Prompt design principles 1. Roles, instructions, constraints - Security and robustness 1. Mitigation and defensive prompting 2. Prompt injection risks
AI for Code and Workflow Optimization		- AI-assisted software development 1. Code generation and debugging 2. SDLC integration - Automation workflows 1. Workflow orchestration concepts 2. API integration basics
Agentic AI Systems		- Agent architecture 1. Autonomous agents and orchestration 2. Multi-step reasoning workflows
AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning

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Cisco AI Technical Practitioner Sample Questions (Q44-Q49):

NEW QUESTION # 44
How does AI support exploratory data analysis when working with large, unstructured datasets?

A. by tuning inference parameters
B. by performing bit-by-bit reconstruction
C. by compressing the datasets
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 # 45
Which workflow mechanism is being used when a company implements a policy where an AI agent can draft a customer email, but a human must authorize the transmission?

A. drift monitoring
B. data lineage
C. approval gate
D. injection mitigation

Answer: C

Explanation:
An approval gate requires human authorization before a high-impact or externally visible action is executed, such as sending an AI-drafted customer email.

NEW QUESTION # 46
Which activity is an indirect prompt injection attack?

A. AI reads a poisoned data source.
B. A prompt forces AI to ignore safety filters.
C. The model generates a false fact.
D. A user types a malicious command.

Answer: A

Explanation:
An indirect prompt injection occurs when malicious instructions are hidden in external content that the AI reads or retrieves, causing the model to follow attacker-controlled instructions from a poisoned data source.

NEW QUESTION # 47
What is the purpose of tokenization in Large Language Models (LLMs)?

A. Splitting text into manageable units
B. Compressing images
C. Encrypting passwords
D. Routing packets

Answer: A

Explanation:
Tokenization converts text into smaller units (tokens) that AI models can process.

NEW QUESTION # 48
Which concept helps reduce overfitting in machine learning?

A. Ignoring datasets
B. Disabling validation
C. Increasing random noise only
D. Regularization

Answer: D

Explanation:
Regularization techniques help models generalize better and avoid memorizing training data.

NEW QUESTION # 49
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