Quiz Cisco - 810-110 - Cisco AI Technical Practitioner–High-quality Free Brain Dumps

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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q57-Q62):

NEW QUESTION # 57
In supervised machine learning, what is required?

Answer: C

Explanation:
Supervised learning trains models using labeled input-output pairs.


NEW QUESTION # 58
What is a use case for generative AI in the testing phase of the software development lifecycle?

Answer: B

Explanation:
Generative AI can create synthetic test data that simulates realistic inputs and edge cases, helping validate application behavior during the testing phase without relying only on production data.


NEW QUESTION # 59
Why are embeddings essential to the retrieval phase of a RAG system?

Answer: B

Explanation:
Embeddings convert text into numerical vectors that capture semantic meaning, allowing a RAG system to retrieve content that is conceptually relevant to the user's query rather than relying only on exact keyword matches.


NEW QUESTION # 60
An organization has regulatory requirements that prohibit any proprietary source code from leaving the internal network. Which hosting strategy provides the highest level of data sovereignty?

Answer: B

Explanation:
Local LLM deployment on internal hardware keeps proprietary source code within the organization's internal network, providing the strongest control over data location, access, and governance.


NEW QUESTION # 61
What is hallucination in generative AI?

Answer: D

Explanation:
Hallucination occurs when an AI confidently produces false or misleading outputs.


NEW QUESTION # 62
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