Pass your actual test at first attempt with Cisco 810-110 training material
Updated: Aug 11, 2026
No. of Questions: 73 Questions & Answers with Testing Engine
Download Limit: Unlimited
Exam-Killer 810-110 updated and latest training material covers the main exam objectives of the actual test, which can ensure you pass easily. Free update for one year of 810-110 training material is available after purchase. Besides, our 810-110 test engine can simulate the actual test environment for better preparation.
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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 |
| Exam Price: | USD 150 |
| Exam Duration: | 60 minutes |
| Passing Score: | Pass/Fail |
| Real Exam Qty: | 40 |
| 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 |
|---|---|---|
| Data Research and Analysis | 15% | - Data collection, preparation and preprocessing - Data visualization and insight generation - Data quality, bias and validation |
| Prompt Engineering | 15% | - Prompt design principles and best practices - Advanced prompting techniques - Defensive prompting and error mitigation |
| AI Ethics and Security | 20% | - Data privacy and security in AI systems - Responsible AI principles - Compliance and governance frameworks - AI-specific threats, risks and misinformation |
| AI for Code and Workflow Optimization | 15% | - Integration of AI tools in development processes - Automation and workflow enhancement - AI-assisted code generation and improvement |
| Agentic AI | 15% | - Model Context Protocol (MCP) framework - Human-in-the-loop strategies - Agent design principles and capabilities - Agentic AI vs Generative AI use cases |
| Generative AI Models | 20% | - Context windows, token limits and response management - Generative AI model families and use cases - Model hosting options and trade-offs - Model selection and evaluation in AI hubs |
1. Which Cisco solution helps automate network operations using AI insights?
A) Cisco Hub
B) Cisco Repeater Utility
C) Cisco BIOS Manager
D) Cisco DNA Center
2. What is a purpose of providing a JSON schema when configuring tool use for an AI agent?
A) to reduce the token count of the agent's system prompt
B) to map relationships between multiple tools in an agent workflow
C) to encrypt the payload before it is sent to the external service
D) to define the required parameters and data types the agent must return
3. A practitioner must reduce the financial cost of a high-volume summarization task. Which strategy addresses token-based billing?
A) expanding the total context window
B) increasing the model temperature
C) minimizing the input prompt size
D) increasing the model sampling rate
4. Which threat involves an attacker intentionally contaminating the training set of a model to influence its future behavior?
A) gradient inversion
B) algorithmic bias
C) data poisoning
D) direct prompt injection
5. Why are prompts important in generative AI systems?
A) They replace training datasets
B) They determine model behavior and output quality
C) They encrypt AI hardware
D) They eliminate hallucinations completely
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: B |
Thank you!
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