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Updated: Aug 08, 2026
No. of Questions: 73 Questions & Answers with Testing Engine
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| Certification Vendor: | Cisco |
| Exam Name: | Cisco AI Technical Practitioner v1.0 (AITECH) |
| Exam Number: | 810-110 |
| Exam Duration: | 60 minutes |
| Real Exam Qty: | 40 |
| Exam Price: | USD 150 |
| Exam Format: | Multiple Choice |
| Passing Score: | Pass/Fail |
| Certificate Validity Period: | 3 years |
| Available Languages: | English |
| 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 for Code and Workflow Optimization | 15% | - AI-assisted code generation and improvement - Automation and workflow enhancement - Integration of AI tools in development processes |
| Topic 2: Generative AI Models | 20% | - Generative AI model families and use cases - Context windows, token limits and response management - Model selection and evaluation in AI hubs - Model hosting options and trade-offs |
| Topic 3: Prompt Engineering | 15% | - Advanced prompting techniques - Defensive prompting and error mitigation - Prompt design principles and best practices |
| Topic 4: Data Research and Analysis | 15% | - Data visualization and insight generation - Data quality, bias and validation - Data collection, preparation and preprocessing |
| Topic 5: AI Ethics and Security | 20% | - Responsible AI principles - Compliance and governance frameworks - Data privacy and security in AI systems - AI-specific threats, risks and misinformation |
| Topic 6: Agentic AI | 15% | - Model Context Protocol (MCP) framework - Agent design principles and capabilities - Human-in-the-loop strategies - Agentic AI vs Generative AI use cases |
1. How does AI support exploratory data analysis when working with large, unstructured datasets?
A) by tuning inference parameters
B) by identifying patterns and groupings
C) by compressing the datasets
D) by performing bit-by-bit reconstruction
2. What is a purpose of providing a JSON schema when configuring tool use for an AI agent?
A) to define the required parameters and data types the agent must return
B) to reduce the token count of the agent's system prompt
C) to map relationships between multiple tools in an agent workflow
D) to encrypt the payload before it is sent to the external service
3. What is the role of the client in the Model Context Protocol?
A) to act as an LLM for inferencing
B) to orchestrate interactions with servers
C) to provide resources for task execution
D) to act as a tool or service provider
4. In supervised machine learning, what is required?
A) Random hardware failures
B) Only encrypted traffic
C) Labeled datasets
D) No data
5. 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
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: C |
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