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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q10-Q15):

NEW QUESTION # 10
Which Cisco technology is commonly associated with network observability and telemetry?

Answer: C

Explanation:
NetFlow provides visibility into traffic flows and is widely used for monitoring, analytics, and AI- driven operations.


NEW QUESTION # 11
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: D

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 # 12
What is occurring when an agent converts a CSV list into a Markdown table for a final report?

Answer: C

Explanation:
Data transformation changes data from one format or structure into another, such as converting CSV rows into a Markdown table for reporting.


NEW QUESTION # 13
Which AI model type is best suited for image recognition tasks?

Answer: B

Explanation:
CNNs are optimized for image and visual pattern recognition.


NEW QUESTION # 14
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 # 15
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