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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Research and Analysis		- Data analysis techniques 1. Statistical analysis 2. Data visualization - Data collection and preparation 1. Data cleaning and preprocessing 2. Data gathering methodologies
Topic 2: Generative AI Models	20%	- Model hosting strategies 1. Cost, latency, privacy, and scalability considerations 2. Cloud-based vs. local deployments - Retrieval Augmented Generation (RAG) 1. Vector databases 2. Embeddings 3. Grounding AI outputs in external knowledge - Major generative model families 1. Diffusion models 2. Large language models (LLMs) - Context windows and token management 1. Response management 2. Token limits - Model selection 1. Selection from AI hubs 2. Reasoning and multimodal tasks - Common use cases 1. Content creation 2. Code generation 3. Text summarization
Topic 3: Agentic AI	20%	- Data transformation and mapping 1. Within AI Agents - AI agent design principles 1. Orchestration 2. Human-in-the-loop (HITL) strategies - Model Context Protocol (MCP) 1. MCP framework primitives 2. Context in agentic AI - Differentiation from Generative AI 1. Autonomous capabilities 2. Use cases comparison
Topic 4: AI Ethics and Security		- Security threats and mitigations 1. Model security 2. Data privacy - Ethical considerations in AI 1. Transparency and explainability 2. Bias and fairness
Topic 5: Prompt Engineering	15%	- Security and safety 1. Reducing hallucinations 2. Prompt injection attacks 3. Improving response accuracy 4. Defensive prompting methods - Principles and patterns 1. Constraints 2. Roles 3. Instructions - Prompting techniques 1. Chained prompting 2. Few-shot prompting 3. Iterative prompting - Prompt structures 1. Text generation 2. Image generation 3. Audio generation
Topic 6: AI for Code and Workflow Optimization		- Workflow automation 1. Process automation 2. Task optimization - AI-assisted code development 1. Code generation 2. Code review and debugging

Cisco AI Technical Practitioner Sample Questions:

Question #1

Which AI concern focuses on protecting sensitive information?

A. Packet fragmentation
B. Clock synchronization
C. Data privacy
D. VLAN tagging

Reveal Solution Discussion 0

Correct Answer: C 🗳️

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Question #2

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

Reveal Solution Discussion 0

Correct Answer: D 🗳️

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Question #3

A developer provides AI with three examples of a log entry mapped to a specific error category before asking AI to categorize a new log entry. Which technique is being used?