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Cisco 810-110 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI for Code and Workflow Optimization | 15% | - Automation and workflow enhancement - AI-assisted code generation and improvement - Integration of AI tools in development processes |
| Topic 2: Data Research and Analysis | 15% | - Data quality, bias and validation - Data visualization and insight generation - Data collection, preparation and preprocessing |
| Topic 3: Agentic AI | 15% | - Human-in-the-loop strategies - Model Context Protocol (MCP) framework - Agentic AI vs Generative AI use cases - Agent design principles and capabilities |
| Topic 4: 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 5: AI Ethics and Security | 20% | - Data privacy and security in AI systems - AI-specific threats, risks and misinformation - Responsible AI principles - Compliance and governance frameworks |
| Topic 6: Prompt Engineering | 15% | - Advanced prompting techniques - Prompt design principles and best practices - Defensive prompting and error mitigation |
Cisco AI Technical Practitioner Sample Questions:
1. What is a purpose of providing a JSON schema when configuring tool use for an AI agent?
A) to encrypt the payload before it is sent to the external service
B) to map relationships between multiple tools in an agent workflow
C) to reduce the token count of the agent's system prompt
D) to define the required parameters and data types the agent must return
2. What is the purpose of a vector database in a RAG architecture?
A) to allocate resources for response generation
B) to perform model weight updates
C) to manage the context window
D) to store numerical representations of data
3. Which Cisco AI capability helps detect abnormal network behavior?
A) BIOS recovery mode
B) Manual packet counting
C) AI-driven anomaly detection
D) Static routing
4. Why is a Human-in-the-Loop requirement essential for AI governance in high-stakes environments like healthcare or finance?
A) to ensure the validity of AI decisions
B) to increase the speed of AI response
C) to protect sensitive customer data
D) to prevent unauthorized access to data
5. Which factor should be considered when selecting a pre-trained model for a mobile application with limited local computational resources?
A) release frequency of the model
B) response creativity level of the model
C) training duration of the model
D) parameter count of the model
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: D |
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