Cisco Cisco AI Technical Practitioner - 810-110 Valid Dumps

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Cisco 810-110 Exam Syllabus Topics:

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

Cisco AI Technical Practitioner Sample Questions:

1. What does NLP stand for in AI?

A) Network Layer Processing
B) Native Logic Programming
C) Natural Language Processing
D) Neural Link Protocol


2. Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?

A) using smaller contexts
B) using known patterns
C) implementing constraints
D) removing system prompts


3. A practitioner must reduce the financial cost of a high-volume summarization task. Which strategy addresses token-based billing?

A) increasing the model sampling rate
B) increasing the model temperature
C) minimizing the input prompt size
D) expanding the total context window


4. Which activity is an agentic AI use case compared to a standard generative AI use case?

A) autonomously fixing a build
B) translating a short email
C) generating a meeting summary
D) writing a poem about routing


5. 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?

A) The number of tokens determines the per-request cost.
B) Costs are determined by the number of API calls.
C) Tokenization increases cost by requiring additional GPU run time.
D) Tokenization has no impact because pricing is based on a flat-rate subscription.


Solutions:

Question # 1
Answer: C
Question # 2
Answer: C
Question # 3
Answer: C
Question # 4
Answer: A
Question # 5
Answer: A

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