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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q23-Q28):

NEW QUESTION # 23
What is the main advantage of cloud-based AI services?

Answer: B

Explanation:
Cloud AI platforms provide scalable infrastructure and elastic computing power for AI workloads.


NEW QUESTION # 24
Which Cisco AI capability helps detect abnormal network behavior?

Answer: B

Explanation:
AI systems can identify unusual patterns and potential threats automatically.


NEW QUESTION # 25
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: B

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 # 26
What is the role of the client in the Model Context Protocol?

Answer: C


NEW QUESTION # 27
Which threat involves an attacker intentionally contaminating the training set of a model to influence its future behavior?

Answer: A

Explanation:
Data poisoning occurs when an attacker deliberately manipulates or contaminates training data so the model learns harmful, biased, or attacker-controlled behavior.


NEW QUESTION # 28
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