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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Data Research and Analysis	15%	- Data quality, bias and validation - Data collection, preparation and preprocessing - Data visualization and insight generation
Prompt Engineering	15%	- Prompt design principles and best practices - Advanced prompting techniques - Defensive prompting and error mitigation
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
Agentic AI	15%	- Agent design principles and capabilities - Human-in-the-loop strategies - Model Context Protocol (MCP) framework - Agentic AI vs Generative AI use cases
AI for Code and Workflow Optimization	15%	- Automation and workflow enhancement - Integration of AI tools in development processes - AI-assisted code generation and improvement
AI Ethics and Security	20%	- AI-specific threats, risks and misinformation - Responsible AI principles - Compliance and governance frameworks - Data privacy and security in AI systems

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Cisco AI Technical Practitioner Sample Questions (Q42-Q47):

NEW QUESTION # 42
What is a corporate data privacy risk when using a public AI chatbot?

A. The AI will provide hallucinated technical specifications.
B. The AI will provide biased technical advice.
C. The data will be encrypted at rest instead of in transit.
D. The input data may be used for model training.

Answer: D

Explanation:
A public AI chatbot may retain submitted corporate data or use it to improve model training, which can expose confidential, proprietary, or regulated information outside the organization's control.

NEW QUESTION # 43
An analyst needs a model that can analyze a network topology diagram and a set of configuration logs simultaneously. Which type of model should be selected?

A. embedding model
B. generative adversarial network
C. multimodal model
D. diffusion model

Answer: C

Explanation:
A multimodal model can process and reason over different input types at the same time, such as images from a network topology diagram and text from configuration logs.

NEW QUESTION # 44
What is fine-tuning in generative AI?

A. Replacing CPUs
B. Encrypting prompts
C. Formatting storage drives
D. Training a pre-trained model on specialized data

Answer: D

Explanation:
Fine-tuning adapts a general AI model to specific domains or business use cases.

NEW QUESTION # 45
Which AI model type is best suited for image recognition tasks?

A. K-Means
B. Decision Tree only
C. Convolutional Neural Network (CNN)
D. Linear Regression

Answer: C

Explanation:
CNNs are optimized for image and visual pattern recognition.

NEW QUESTION # 46
Which approach protects PII when utilizing a public AI service for data analysis?

A. ensuring the AI provider maintains industry-standard SOC 2 compliance
B. anonymizing or redacting PH from the dataset before transmitting the request
C. encrypting the data payload during transit to the AI service provider
D. utilizing system prompts to instruct the AI to ignore sensitive data fields

Answer: B

Explanation:
Anonymizing or redacting sensitive personal information before sending data to a public AI service prevents PII from being exposed outside the organization's controlled environment.

NEW QUESTION # 47
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