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Updated: Aug 15, 2026
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| Certification Vendor: | Cisco |
| Exam Name: | Cisco AI Technical Practitioner v1.0 (AITECH) |
| Exam Number: | 810-110 |
| Exam Format: | Multiple Choice |
| Available Languages: | English |
| Certificate Validity Period: | 3 years |
| Passing Score: | Pass/Fail |
| Exam Duration: | 60 minutes |
| Real Exam Qty: | 40 |
| Exam Price: | USD 150 |
| Recommended Training: | Cisco AI Technical Practitioner Training |
| Exam Registration: | Cisco Official Exam Page |
| Sample Questions: | Cisco 810-110 Sample Questions |
| Exam Way: | Online proctored or at authorized test centers |
| Pre Condition: | No formal prerequisites |
| Official Syllabus URL: | https://learningcontent.cisco.com/documents/marketing/exam-topics/810-110-AITECH-v1.0.pdf |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Ethics and Security | 20% | - Data privacy and security in AI systems - Compliance and governance frameworks - Responsible AI principles - AI-specific threats, risks and misinformation |
| Topic 2: Agentic AI | 15% | - Human-in-the-loop strategies - Agent design principles and capabilities - Model Context Protocol (MCP) framework - Agentic AI vs Generative AI use cases |
| Topic 3: Generative AI Models | 20% | - Model hosting options and trade-offs - Context windows, token limits and response management - Generative AI model families and use cases - Model selection and evaluation in AI hubs |
| Topic 4: Data Research and Analysis | 15% | - Data collection, preparation and preprocessing - Data visualization and insight generation - Data quality, bias and validation |
| Topic 5: AI for Code and Workflow Optimization | 15% | - Integration of AI tools in development processes - Automation and workflow enhancement - AI-assisted code generation and improvement |
| Topic 6: Prompt Engineering | 15% | - Advanced prompting techniques - Defensive prompting and error mitigation - Prompt design principles and best practices |
1. Which AI concern focuses on protecting sensitive information?
A) Data privacy
B) VLAN tagging
C) Packet fragmentation
D) Clock synchronization
2. What is the purpose of tokenization in Large Language Models (LLMs)?
A) Routing packets
B) Compressing images
C) Splitting text into manageable units
D) Encrypting passwords
3. What is an advantage of cloud-hosted API services when comparing cloud-hosted and locally hosted AI models?
A) elimination of per-token operational costs
B) lower network latency for all end users
C) rapid elastic scaling for unpredictable inference demand
D) full control over data residency and privacy
4. Which risk occurs when an AI model provides an outdated technical specification because it was trained before the new standard was released?
A) disinformation
B) data poisoning
C) misinformation
D) knowledge cut-off
5. In an AI-powered automation workflow, what is the function of an approval gate?
A) to trigger automated completion notifications to project stakeholders
B) to automatically block deployments if system health alerts are active
C) to ensure the internal logic of AI remains closed for modification
D) to apply human judgement before high-impact actions are executed
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: D |
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