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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prompt Engineering15%- Principles and patterns
  • 1. Instructions
  • 2. Constraints
  • 3. Roles
- Security and safety
  • 1. Reducing hallucinations
  • 2. Improving response accuracy
  • 3. Prompt injection attacks
  • 4. Defensive prompting methods
- Prompting techniques
  • 1. Iterative prompting
  • 2. Few-shot prompting
  • 3. Chained prompting
- Prompt structures
  • 1. Text generation
  • 2. Image generation
  • 3. Audio generation
Topic 2: Generative AI Models20%- Major generative model families
  • 1. Large language models (LLMs)
  • 2. Diffusion models
- 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
- Common use cases
  • 1. Text summarization
  • 2. Content creation
  • 3. Code generation
- Retrieval Augmented Generation (RAG)
  • 1. Vector databases
  • 2. Grounding AI outputs in external knowledge
  • 3. Embeddings
- Context windows and token management
  • 1. Response management
  • 2. Token limits
Topic 3: Data Research and Analysis- Data collection and preparation
  • 1. Data cleaning and preprocessing
  • 2. Data gathering methodologies
- Data analysis techniques
  • 1. Data visualization
  • 2. Statistical analysis
Topic 4: AI for Code and Workflow Optimization- AI-assisted code development
  • 1. Code review and debugging
  • 2. Code generation
- Workflow automation
  • 1. Task optimization
  • 2. Process automation
Topic 5: Agentic AI20%- 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
- Data transformation and mapping
  • 1. Within AI Agents
Topic 6: 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

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Cisco AI Technical Practitioner Sample Questions (Q35-Q40):

NEW QUESTION # 35
Which protocol is commonly used for streaming telemetry in modern networks?

Answer: A

Explanation:
gRPC supports efficient real-time telemetry streaming in modern network automation environments.


NEW QUESTION # 36
What is a purpose of providing a JSON schema when configuring tool use for an AI agent?

Answer: D

Explanation:
A JSON schema defines the structure, required fields, and data types for tool calls, helping the agent provide valid inputs or outputs that the external tool can process reliably.


NEW QUESTION # 37
Why are embeddings essential to the retrieval phase of a RAG system?

Answer: D

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 # 38
What is a use case for generative AI in the testing phase of the software development lifecycle?

Answer: C

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 # 39
What is an advantage of cloud-hosted API services when comparing cloud-hosted and locally hosted AI models?

Answer: A

Explanation:
Cloud-hosted API services can scale inference capacity quickly based on demand, making them suitable for workloads with unpredictable or fluctuating usage.


NEW QUESTION # 40
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