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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q11-Q16):

NEW QUESTION # 11
What is the role of embeddings in AI systems?

Answer: C

Explanation:
Embeddings convert text or objects into vectors that capture semantic meaning.


NEW QUESTION # 12
What does NLP stand for in AI?

Answer: B

Explanation:
NLP enables computers to understand and generate human language.


NEW QUESTION # 13
Which Cisco solution helps automate network operations using AI insights?

Answer: A

Explanation:
Cisco DNA Center uses AI and analytics for intent-based networking and automation.


NEW QUESTION # 14
Which Cisco platform provides AI-powered security analytics?

Answer: C

Explanation:
Cisco SecureX integrates security visibility, analytics, and automation using AI-driven insights.


NEW QUESTION # 15
A marketing team must generate high-fidelity images for a new product launch. Which model is designed to handle this task through the process of iterative noise reduction?

Answer: A

Explanation:
Diffusion models generate high-fidelity images by starting from noise and iteratively denoising it over multiple steps until a coherent image is produced.


NEW QUESTION # 16
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