Cisco 810-110題庫，810-110考試內容

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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Agentic AI20%- Model Context Protocol (MCP)
  • 1. Context in agentic AI
  • 2. MCP framework primitives
- Differentiation from Generative AI
  • 1. Autonomous capabilities
  • 2. Use cases comparison
- Data transformation and mapping
  • 1. Within AI Agents
- AI agent design principles
  • 1. Orchestration
  • 2. Human-in-the-loop (HITL) strategies
Topic 2: Data Research and Analysis- Data analysis techniques
  • 1. Statistical analysis
  • 2. Data visualization
- Data collection and preparation
  • 1. Data gathering methodologies
  • 2. Data cleaning and preprocessing
Topic 3: Generative AI Models20%- Model selection
  • 1. Reasoning and multimodal tasks
  • 2. Selection from AI hubs
- Model hosting strategies
  • 1. Cost, latency, privacy, and scalability considerations
  • 2. Cloud-based vs. local deployments
- Major generative model families
  • 1. Diffusion models
  • 2. Large language models (LLMs)
- Context windows and token management
  • 1. Token limits
  • 2. Response management
- Retrieval Augmented Generation (RAG)
  • 1. Grounding AI outputs in external knowledge
  • 2. Vector databases
  • 3. Embeddings
- Common use cases
  • 1. Text summarization
  • 2. Content creation
  • 3. Code generation
Topic 4: Prompt Engineering15%- Principles and patterns
  • 1. Roles
  • 2. Instructions
  • 3. Constraints
- Prompt structures
  • 1. Audio generation
  • 2. Text generation
  • 3. Image generation
- Prompting techniques
  • 1. Iterative prompting
  • 2. Chained prompting
  • 3. Few-shot prompting
- Security and safety
  • 1. Reducing hallucinations
  • 2. Prompt injection attacks
  • 3. Improving response accuracy
  • 4. Defensive prompting methods
Topic 5: AI Ethics and Security- Security threats and mitigations
  • 1. Data privacy
  • 2. Model security
- Ethical considerations in AI
  • 1. Transparency and explainability
  • 2. Bias and fairness
Topic 6: AI for Code and Workflow Optimization- Workflow automation
  • 1. Task optimization
  • 2. Process automation
- AI-assisted code development
  • 1. Code review and debugging
  • 2. Code generation

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最新的 Cisco AI Technical Practitioner (AITECH) 810-110 免費考試真題 (Q14-Q19):

問題 #14
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?

答案：B

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


問題 #15
Which concept helps reduce overfitting in machine learning?

答案：B

解題說明：
Regularization techniques help models generalize better and avoid memorizing training data.


問題 #16
A team uses AI to scaffold a new microservice. What does this process involve?

答案：C

解題說明：
Scaffolding uses AI to generate the initial project structure, boilerplate files, configuration, and basic code layout so the team can start development faster.


問題 #17
Which Cisco platform provides AI-powered security analytics?

答案：B

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


問題 #18
Why is defining a persona considered a best practice for technical prompt engineering?

答案：C

解題說明：
Defining a persona guides the AI to respond with the appropriate role-based tone, vocabulary, level of technical depth, and communication style for the intended audience.


問題 #19
......

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