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Cisco 810-110 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Research and Analysis | 15% | - Data quality, bias and validation - Data visualization and insight generation - Data collection, preparation and preprocessing |
| Topic 2: Generative AI Models | 20% | - Model selection and evaluation in AI hubs - Context windows, token limits and response management - Model hosting options and trade-offs - Generative AI model families and use cases |
| Topic 3: Prompt Engineering | 15% | - Defensive prompting and error mitigation - Advanced prompting techniques - Prompt design principles and best practices |
| Topic 4: Agentic AI | 15% | - Agent design principles and capabilities - Human-in-the-loop strategies - Agentic AI vs Generative AI use cases - Model Context Protocol (MCP) framework |
| Topic 5: AI for Code and Workflow Optimization | 15% | - AI-assisted code generation and improvement - Integration of AI tools in development processes - Automation and workflow enhancement |
| Topic 6: AI Ethics and Security | 20% | - Data privacy and security in AI systems - Compliance and governance frameworks - AI-specific threats, risks and misinformation - Responsible AI principles |
Cisco AI Technical Practitioner Sample Questions:
1. A practitioner is estimating the operational cost of integrating a cloud-hosted LLM API into an application. How does tokenization influence the cost of using this API?
A) Costs are determined by the number of API calls.
B) Tokenization increases cost by requiring additional GPU run time.
C) The number of tokens determines the per-request cost.
D) Tokenization has no impact because pricing is based on a flat-rate subscription.
2. Which AI-assisted task standardizes inconsistent date formats (e.g., MM/DD/YY and DD-MM- YYYY)?
A) data correlation
B) data visualization
C) data transformation
D) thematic summarization
3. What is aggregation bias in the context of AI-assisted data analysis?
A) when AI fails to combine conflicting patterns
B) when a summary masks subpatterns
C) when data is omitted due to incompatible formats
D) when AI uses summary statistics instead of raw data
4. Which generative AI model family should be used for identifying and summarizing technical themes across thousands of unstructured network incident reports?
A) generative adversarial networks
B) large language models
C) variational autoencoders
D) diffusion models
5. A team uses AI to scaffold a new microservice. What does this process involve?
A) generating the initial structure
B) testing the final production code
C) creating automated deployment scripts
D) removing redundant logic
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: A |






