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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Agentic AI20%- Model Context Protocol (MCP)
  • 1. MCP framework primitives
  • 2. Context in agentic AI
- AI agent design principles
  • 1. Human-in-the-loop (HITL) strategies
  • 2. Orchestration
- Differentiation from Generative AI
  • 1. Use cases comparison
  • 2. Autonomous capabilities
- Data transformation and mapping
  • 1. Within AI Agents
Topic 2: Prompt Engineering15%- Prompting techniques
  • 1. Few-shot prompting
  • 2. Iterative prompting
  • 3. Chained prompting
- Prompt structures
  • 1. Text generation
  • 2. Audio generation
  • 3. Image generation
- Principles and patterns
  • 1. Constraints
  • 2. Roles
  • 3. Instructions
- Security and safety
  • 1. Defensive prompting methods
  • 2. Prompt injection attacks
  • 3. Improving response accuracy
  • 4. Reducing hallucinations
Topic 3: Data Research and Analysis- Data collection and preparation
  • 1. Data gathering methodologies
  • 2. Data cleaning and preprocessing
- Data analysis techniques
  • 1. Statistical analysis
  • 2. Data visualization
Topic 4: AI for Code and Workflow Optimization- Workflow automation
  • 1. Task optimization
  • 2. Process automation
- AI-assisted code development
  • 1. Code review and debugging
  • 2. Code generation
Topic 5: Generative AI Models20%- Retrieval Augmented Generation (RAG)
  • 1. Grounding AI outputs in external knowledge
  • 2. Vector databases
  • 3. Embeddings
- Common use cases
  • 1. Content creation
  • 2. Code generation
  • 3. Text summarization
- Model selection
  • 1. Selection from AI hubs
  • 2. Reasoning and multimodal tasks
- Major generative model families
  • 1. Diffusion models
  • 2. Large language models (LLMs)
- Model hosting strategies
  • 1. Cloud-based vs. local deployments
  • 2. Cost, latency, privacy, and scalability considerations
- Context windows and token management
  • 1. Response management
  • 2. Token limits
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 (Q71-Q76):

NEW QUESTION # 71
A user includes project background information and the specific technical constraints in a prompt.
Which principle of prompt engineering is being applied?

Answer: B

Explanation:
Describing the situation means providing relevant context, background information, and constraints so the AI can generate a response that fits the specific scenario.


NEW QUESTION # 72
A practitioner uses self-consistency by running the same prompt three times and comparing the results. What is the goal of this strategy?

Answer: C

Explanation:
Self-consistency compares multiple responses to the same prompt to check whether the model produces stable, reliable results across repeated runs.


NEW QUESTION # 73
What is the benefit of AI Ops (AIOps) in networking?

Answer: D

Explanation:
AIOps uses AI to improve IT operations, detect anomalies, and accelerate troubleshooting.


NEW QUESTION # 74
Which activity is an indirect prompt injection attack?

Answer: C

Explanation:
An indirect prompt injection occurs when malicious instructions are hidden in external content that the AI reads or retrieves, causing the model to follow attacker-controlled instructions from a poisoned data source.


NEW QUESTION # 75
Which software development lifecycle phase utilizes AI to analyze stakeholder documentation for logical inconsistencies and to draft structured user stories?

Answer: B

Explanation:
In the requirements phase, AI can analyze stakeholder documentation to identify logical gaps or inconsistencies and help convert business needs into structured user stories.


NEW QUESTION # 76
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