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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner Sample Questions (Q50-Q55):

NEW QUESTION # 50
A practitioner uses self-consistency by running the same prompt three times and comparing the results. What is the goal of this strategy?

A. to bypass the context window
B. to increase the model creativity
C. to verify the output reliability
D. to increase the response speed

Answer: C

Explanation:
Self-consistency compares multiple responses to the same prompt to check whether the model produces stable, reliable results across repeated runs.

NEW QUESTION # 51
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. cloud-based API with Zero Data Retention
B. managed SaaS AI platform with SOC 2 audit
C. local LLM deployment on internal hardware
D. hybrid deployment with cloud-based backup

Answer: C

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 # 52
Which AI model type is best suited for image recognition tasks?

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

Answer: D

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

NEW QUESTION # 53
Which approach protects PII when utilizing a public AI service for data analysis?

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

Answer: D

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 # 54
Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?

A. removing system prompts
B. using known patterns
C. implementing constraints
D. using smaller contexts

Answer: C

Explanation:
Implementing constraints, such as maximum iteration limits, stop conditions, and execution boundaries, helps prevent an autonomous agent from repeatedly running actions without reaching a valid endpoint.

NEW QUESTION # 55
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