AI-201日本語試験情報 & AI-201参考書内容

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Salesforce AI-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Einstein Trust Layer & Security- Data Masking
  • 1. Configuration of privacy data entities
- Trust Layer & Security Features
  • 1. Enterprise-grade deployment
Topic 2: Prompt Engineering30%- Prompt Builder & Template Creation
  • 1. Best practices
- Agentforce AI Setup & Configuration
  • 1. Advanced implementation strategies
Topic 3: Reasoning Engine & AI Actions- Workflow mastery
  • 1. Custom Agent actions (Apex)
  • 2. Standard Agent actions
  • 3. Custom Agent actions (Flows)
Topic 4: Agent Force Concepts30%- Data Cloud & Grounding Techniques
  • 1. Real-world applications
- Einstein GPT Integration
  • 1. Advanced implementation strategies

>> AI-201日本語試験情報 <<

100％合格率のAI-201日本語試験情報試験-試験の準備方法-素晴らしいAI-201参考書内容

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Salesforce Certified Agentforce Specialist 認定 AI-201 試験問題 (Q197-Q202):

質問 # 197
What is the main benefit of using a Knowledge article in an Agentforce Data Library?

正解：C

解説：
Why is "A structured, searchable repository of approved documents" the correct answer?
Using a Knowledge Article in an Agentforce Data Library ensures that agents can quickly access reliable and pre-approved information during customer interactions.
Key Benefits of Knowledge Articles in an Agentforce Data Library:
Ensures Information Accuracy and Consistency
Knowledge articles provide approved, well-structured responses, reducing the risk of misinformation.
This ensures customer service consistency across different agents.
Improves Searchability and AI-Grounded Responses
Articles are indexed and retrieved efficiently by AI-powered search engines.
AI-generated responses are grounded in accurate, structured knowledge, improving response quality.
Enhances Customer Support and Agent Productivity
Agents spend less time searching for information and more time resolving customer inquiries.
Einstein AI can suggest the most relevant articles based on conversation context.


質問 # 198
Universal Containers is very concerned about security compliance and wants to understand:
- Which prompt text is sent to the large language model (LLM)
- How it is masked
- The masked response
What should the Agentforce Specialist recommend?

正解：A

解説：
To address security compliance concerns and provide visibility into the prompt text sent to the LLM, how it is masked, and the masked response, the Agentforce Specialist should recommend enabling the audit trail in the Einstein Trust Layer. This feature captures and logs the prompts sent to the large language model (LLM) along with the masking of sensitive information and the AI's response. This audit trail ensures full transparency and compliance with security requirements.


質問 # 199
Universal Containers (UC) wants to ensure its compliance team can retrieve exact matches of policy clause numbers from a structured legal document library. Which search type should UC implement?

正解：B

解説：
According to the AgentForce Search Optimization Guide, when the use case requires retrieving exact matches (such as policy clause numbers, legal identifiers, or invoice IDs) from structured data, the recommended approach is to use keyword search. The documentation specifies:
"Keyword search ensures deterministic retrieval of exact term matches from structured fields, preserving precision for identifiers, numeric values, and code references."


質問 # 200
Universal Containers aims to streamline the sales team's daily tasks by using AI. When considering these new workflows, which improvement requires the use of Prompt Builder?

正解：A

解説：
Prompt Builder is explicitly required to create AI-generated summary fields via prompt templates.
These fields use natural language instructions to extract or synthesize information (e.g., summarizing contract terms). Time-to-close estimations (A) and lead scores (C) are typically handled by predictive AI (e.g., Einstein Opportunity Scoring) or analytics tools, which do not require Prompt Builder.


質問 # 201
An Al Specialist is tasked with configuring a generative model to create personalized sales emails using customer data stored in Salesforce. The AI Specialist has already fine-tuned a large language model (LLM) on the OpenAI platform. Security and data privacy are critical concerns for the client. How should the Agentforce Specialist integrate the custom LLM into Salesforce?

正解：B

解説：
Since security and data privacy are critical, the best option for the Agentforce Specialist is to integrate the fine-tuned LLM (Large Language Model) into Salesforce by adding it to Einstein Studio Model Builder. Einstein Studio allows organizations to bring their own AI models (BYOM), ensuring the model is securely managed within Salesforce's environment, adhering to data privacy standards.


質問 # 202
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