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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Ethics and Security- Ethical considerations in AI
  • 1. Transparency and explainability
  • 2. Bias and fairness
- Security threats and mitigations
  • 1. Data privacy
  • 2. Model security
Topic 2: Agentic AI20%- Model Context Protocol (MCP)
  • 1. MCP framework primitives
  • 2. Context in agentic AI
- Data transformation and mapping
  • 1. Within AI Agents
- AI agent design principles
  • 1. Orchestration
  • 2. Human-in-the-loop (HITL) strategies
- Differentiation from Generative AI
  • 1. Autonomous capabilities
  • 2. Use cases comparison
Topic 3: Prompt Engineering15%- Security and safety
  • 1. Defensive prompting methods
  • 2. Prompt injection attacks
  • 3. Reducing hallucinations
  • 4. Improving response accuracy
- Principles and patterns
  • 1. Roles
  • 2. Instructions
  • 3. Constraints
- Prompting techniques
  • 1. Iterative prompting
  • 2. Chained prompting
  • 3. Few-shot prompting
- Prompt structures
  • 1. Image generation
  • 2. Text generation
  • 3. Audio generation
Topic 4: Data Research and Analysis- Data analysis techniques
  • 1. Statistical analysis
  • 2. Data visualization
- Data collection and preparation
  • 1. Data cleaning and preprocessing
  • 2. Data gathering methodologies
Topic 5: Generative AI Models20%- Retrieval Augmented Generation (RAG)
  • 1. Vector databases
  • 2. Embeddings
  • 3. Grounding AI outputs in external knowledge
- Common use cases
  • 1. Text summarization
  • 2. Content creation
  • 3. Code generation
- Context windows and token management
  • 1. Token limits
  • 2. Response management
- Major generative model families
  • 1. Diffusion models
  • 2. Large language models (LLMs)
- 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
Topic 6: AI for Code and Workflow Optimization- AI-assisted code development
  • 1. Code generation
  • 2. Code review and debugging
- Workflow automation
  • 1. Process automation
  • 2. Task optimization

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

NEW QUESTION # 51
What is occurring when an agent converts a CSV list into a Markdown table for a final report?

Answer: A

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 # 52
Which AI-driven activity involves a developer providing runtime error logs to a model to receive an explanation of the root cause and a suggested fix?

Answer: D

Explanation:
AI-assisted debugging uses error logs, stack traces, and runtime context to help identify the root cause of a failure and suggest a corrective fix.


NEW QUESTION # 53
Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?

Answer: B

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 # 54
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: D

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 # 55
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 # 56
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