Free PDF 2026 Cisco Professional Online 810-110 Bootcamps

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Cisco 810-110 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Research and Analysis- Data collection and preparation
  • 1. Data cleaning and preprocessing
  • 2. Data gathering methodologies
- Data analysis techniques
  • 1. Statistical analysis
  • 2. Data visualization
Topic 2: Prompt Engineering15%- Security and safety
  • 1. Improving response accuracy
  • 2. Reducing hallucinations
  • 3. Defensive prompting methods
  • 4. Prompt injection attacks
- Prompting techniques
  • 1. Chained prompting
  • 2. Few-shot prompting
  • 3. Iterative prompting
- Prompt structures
  • 1. Text generation
  • 2. Image generation
  • 3. Audio generation
- Principles and patterns
  • 1. Constraints
  • 2. Roles
  • 3. Instructions
Topic 3: 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
Topic 4: Agentic AI20%- Differentiation from Generative AI
  • 1. Autonomous capabilities
  • 2. Use cases comparison
- Model Context Protocol (MCP)
  • 1. Context in agentic AI
  • 2. MCP framework primitives
- Data transformation and mapping
  • 1. Within AI Agents
- AI agent design principles
  • 1. Human-in-the-loop (HITL) strategies
  • 2. Orchestration
Topic 5: Generative AI Models20%- Retrieval Augmented Generation (RAG)
  • 1. Vector databases
  • 2. Embeddings
  • 3. Grounding AI outputs in external knowledge
- Model selection
  • 1. Selection from AI hubs
  • 2. Reasoning and multimodal tasks
- Context windows and token management
  • 1. Token limits
  • 2. Response management
- Model hosting strategies
  • 1. Cloud-based vs. local deployments
  • 2. Cost, latency, privacy, and scalability considerations
- Major generative model families
  • 1. Diffusion models
  • 2. Large language models (LLMs)
- Common use cases
  • 1. Text summarization
  • 2. Code generation
  • 3. Content creation
Topic 6: 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

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Exam 810-110 Objectives | Related 810-110 Exams

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Cisco AI Technical Practitioner Sample Questions (Q53-Q58):

NEW QUESTION # 53
Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?

Answer: A

Explanation:
Knowledge cut-off occurs when a model lacks information about events, standards, or specifications released after its training data period, causing it to provide outdated information.


NEW QUESTION # 54
Which workflow mechanism is being used when a company implements a policy where an AI agent can draft a customer email, but a human must authorize the transmission?

Answer: A

Explanation:
An approval gate requires human authorization before a high-impact or externally visible action is executed, such as sending an AI-drafted customer email.


NEW QUESTION # 55
What is the primary goal of Retrieval-Augmented Generation (RAG) in AI systems?

Answer: A

Explanation:
RAG combines a large language model with external data retrieval systems so the model can answer using updated and domain-specific knowledge.


NEW QUESTION # 56
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?

Answer: D

Explanation:
Prompt chaining breaks a complex task into a sequence of connected prompts, where each response becomes part of the input for the next step.


NEW QUESTION # 57
How does context window management help control the cost of a long-running AI conversation?

Answer: A

Explanation:
Context window management controls cost by limiting how much prior conversation history is included with each new request, reducing the number of input tokens processed and billed.


NEW QUESTION # 58
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