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Exam Code: 810-110
Exam Name: Cisco AI Technical Practitioner
Certification Provider: Cisco
Corresponding Certification: Cisco AI Technical Practitioner (AITECH)

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810-110

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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Generative AI Models20%- Retrieval Augmented Generation (RAG)
  • 1. Embeddings
  • 2. Grounding AI outputs in external knowledge
  • 3. Vector databases
- Common use cases
  • 1. Text summarization
  • 2. Content creation
  • 3. Code generation
- 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
- Context windows and token management
  • 1. Response management
  • 2. Token limits
- Major generative model families
  • 1. Diffusion models
  • 2. Large language models (LLMs)
AI for Code and Workflow Optimization- Workflow automation
  • 1. Process automation
  • 2. Task optimization
- AI-assisted code development
  • 1. Code review and debugging
  • 2. Code generation
Agentic AI20%- 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. Context in agentic AI
  • 2. MCP framework primitives
- Differentiation from Generative AI
  • 1. Autonomous capabilities
  • 2. Use cases comparison
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
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
Prompt Engineering15%- Principles and patterns
  • 1. Roles
  • 2. Instructions
  • 3. Constraints
- Prompting techniques
  • 1. Chained prompting
  • 2. Iterative prompting
  • 3. Few-shot prompting
- Security and safety
  • 1. Reducing hallucinations
  • 2. Prompt injection attacks
  • 3. Defensive prompting methods
  • 4. Improving response accuracy
- Prompt structures
  • 1. Text generation
  • 2. Audio generation
  • 3. Image generation

Cisco AI Technical Practitioner Sample Questions:

Question 1

What is an advantage of cloud-hosted API services when comparing cloud-hosted and locally hosted AI models?

A. rapid elastic scaling for unpredictable inference demand
B. full control over data residency and privacy
C. elimination of per-token operational costs
D. lower network latency for all end users


Question 2

Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?

A. misinformation
B. knowledge cut-off
C. data poisoning
D. disinformation


Question 3

Which concept helps reduce overfitting in machine learning?

A. Ignoring datasets
B. Regularization
C. Increasing random noise only
D. Disabling validation


Question 4

A practitioner is solving a complex architectural problem by breaking it into four sequential prompts. Each prompt's output is fed as input into the next prompt in the sequence. Which prompt engineering technique is being used?

A. chain-of-thought prompting
B. meta-prompting
C. prompt chaining
D. few-shot prompting


Question 5

What is the purpose of tokenization in Large Language Models (LLMs)?

A. Encrypting passwords
B. Routing packets
C. Compressing images
D. Splitting text into manageable units


Solutions:

Question 1
Answer: A		Question 2
Answer: B		Question 3
Answer: B		Question 4
Answer: C		Question 5
Answer: D

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