Quiz 810-110 - Cisco AI Technical Practitioner–High Pass-Rate Free Exam Questions

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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q51-Q56):

NEW QUESTION # 51
A company discloses to its users that their support tickets are being summarized by an AI model.
Which responsible AI principle does this action support?

Answer: B

Explanation:
Transparency means clearly informing users when AI is being used, what it is doing, and how it may affect their data or experience.


NEW QUESTION # 52
What is the role of embeddings in AI systems?

Answer: B


NEW QUESTION # 53
A practitioner is estimating the operational cost of integrating a cloud-hosted LLM API into an application. How does tokenization influence the cost of using this API?

Answer: A

Explanation:
Cloud-hosted LLM APIs commonly charge based on the number of input and output tokens processed, so tokenization directly affects the per-request cost.


NEW QUESTION # 54
Why is a Human-in-the-Loop requirement essential for AI governance in high-stakes environments like healthcare or finance?

Answer: C

Explanation:
Human-in-the-Loop governance ensures that a qualified person reviews, validates, and can override AI-generated decisions when outcomes may significantly affect people, such as medical diagnoses, treatment decisions, credit approvals, or financial risk assessments.


NEW QUESTION # 55
Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?

Answer: D

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 # 56
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