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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning
Topic 2: Prompt Engineering	15%	- Prompt design principles 1. Roles, instructions, constraints - Security and robustness 1. Mitigation and defensive prompting 2. Prompt injection risks - Prompting techniques 1. Few-shot prompting 2. Chained and iterative prompting
Topic 3: Ethics and Security	15%	- Data privacy and governance 1. Secure AI data handling - Responsible AI principles 1. Fairness, transparency, accountability 2. Bias mitigation - AI security threats 1. AI-specific attack surfaces 2. Misinformation and hallucinations
Topic 4: AI for Code and Workflow Optimization		- Automation workflows 1. Workflow orchestration concepts 2. API integration basics - AI-assisted software development 1. Code generation and debugging 2. SDLC integration
Topic 5: Agentic AI Systems		- Agent architecture 1. Multi-step reasoning workflows 2. Autonomous agents and orchestration
Topic 6: Generative AI Models	20%	- Model fundamentals and use cases 1. Use cases: summarization, code generation, content creation 2. LLMs and diffusion models overview - Model hosting and architecture 1. Latency, cost, privacy considerations 2. Cloud vs local deployment trade-offs - Context and retrieval systems 1. Context windows and token limits 2. RAG, embeddings, vector databases

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Cisco AI Technical Practitioner Sample Questions (Q30-Q35):

NEW QUESTION # 30
An organization has regulatory requirements that prohibit any proprietary source code from leaving the internal network. Which hosting strategy provides the highest level of data sovereignty?

A. local LLM deployment on internal hardware
B. hybrid deployment with cloud-based backup
C. cloud-based API with Zero Data Retention
D. managed SaaS AI platform with SOC 2 audit

Answer: A

Explanation:
Local LLM deployment on internal hardware keeps proprietary source code within the organization's internal network, providing the strongest control over data location, access, and governance.

NEW QUESTION # 31
What is the primary goal of Retrieval-Augmented Generation (RAG) in AI systems?

A. Replace neural networks
B. Improve model responses with external knowledge
C. Encrypt AI datasets
D. Reduce GPU usage only

Answer: B

Explanation:
RAG combines a large language model with external data retrieval systems so the model can answer using updated and domain-specific knowledge.

NEW QUESTION # 32
A user includes project background information and the specific technical constraints in a prompt.
Which principle of prompt engineering is being applied?

A. describing the situation
B. using few-shot
C. defining a persona
D. stating the purpose

Answer: A

Explanation:
Describing the situation means providing relevant context, background information, and constraints so the AI can generate a response that fits the specific scenario.

NEW QUESTION # 33
Which AI model type is best suited for image recognition tasks?

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

Answer: D

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

NEW QUESTION # 34
A marketing team must generate high-fidelity images for a new product launch. Which model is designed to handle this task through the process of iterative noise reduction?

A. large language models
B. variational autoencoders
C. generative adversarial networks
D. diffusion models

Answer: D

Explanation:
Diffusion models generate high-fidelity images by starting from noise and iteratively denoising it over multiple steps until a coherent image is produced.

NEW QUESTION # 35
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