810-110試験番号 & 810-110ダウンロード

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Cisco 810-110 Exam Syllabus Topics:

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

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Cisco AI Technical Practitioner 認定 810-110 試験問題 (Q53-Q58):

質問 # 53
Which AI-assisted task standardizes inconsistent date formats (e.g., MM/DD/YY and DD-MM- YYYY)?

A. data transformation
B. thematic summarization
C. data visualization
D. data correlation

正解：A

解説：
Data transformation converts inconsistent data into a consistent format, such as standardizing multiple date formats into one required representation.

質問 # 54
In supervised machine learning, what is required?

A. Labeled datasets
B. Only encrypted traffic
C. No data
D. Random hardware failures

正解：A

解説：
Supervised learning trains models using labeled input-output pairs.

質問 # 55
Which metric is commonly used to evaluate classification models?

A. Voltage
B. Packet TTL
C. Throughput only
D. Accuracy

正解：D

解説：
Accuracy measures how many predictions were correct out of total predictions.

質問 # 56
What happens when the input provided to an LLM exceeds its context window limit?

A. The model switches to a different algorithm.
B. The model caches the overflow data.
C. The model increases its context window size.
D. The model loses the earliest part of the text.

正解：D

解説：
When input exceeds the context window, the model cannot process all provided text at once, so earlier content may be truncated or pushed out of the active context.

質問 # 57
A user includes project background information and the specific technical constraints in a prompt.
Which principle of prompt engineering is being applied?

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

正解：B

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

質問 # 58
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