Purchase Cisco : 810-110 Exam Materials and then pass exam easily

Last Updated: Aug 09, 2026

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Cisco 810-110 Exam Syllabus Topics:

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

Cisco AI Technical Practitioner Sample Questions:

1. 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) prompt chaining
C) meta-prompting
D) few-shot prompting


2. When using AI to draft a technical proposal, what is the benefit of a format-agnostic strategy?

A) It minimizes token consumption.
B) It allows for easy repurposing.
C) It maintains contextual alignment.
D) It ensures the most creative text.


3. Which AI concern focuses on protecting sensitive information?

A) Packet fragmentation
B) VLAN tagging
C) Clock synchronization
D) Data privacy


4. What is a corporate data privacy risk when using a public AI chatbot?

A) The data will be encrypted at rest instead of in transit.
B) The AI will provide biased technical advice.
C) The input data may be used for model training.
D) The AI will provide hallucinated technical specifications.


5. What is the role of embeddings in AI systems?

A) Assigning IP addresses
B) Compressing logs
C) Encrypting traffic
D) Representing data numerically in vector space


Solutions:

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

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