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Google Generative-AI-Leader日本語 Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Generative AI Leader Certification Exam
Exam Number:Generative-AI-Leader
Passing Score:Not publicly disclosed
Real Exam Qty:50-60
Exam Price:USD 99 (plus tax where applicable)
Certificate Validity Period:3 years
Exam Duration:90 minutes
Exam Format:Multiple choice
Available Languages:Japanese, Spanish, Portuguese, English
Recommended Training:Generative AI Leader Study Guide
Generative AI Leader Training Course
Exam Registration:Google Cloud Certification Registration
Sample Questions: DOWNLOAD DEMO
Exam Way:Online-proctored or onsite-proctored
Pre Condition:No prerequisites required; open to all roles and backgrounds
Official Syllabus URL:https://cloud.google.com/learn/certification/generative-ai-leader

Google Generative-AI-Leader日本語 Exam Syllabus Topics:

SectionWeightObjectives
Fundamentals of Generative AI30%- Core concepts and characteristics of generative AI
- Responsible AI principles and application
- Key technologies and differences from traditional AI
- Foundation models: definition, capabilities, and use cases
Google Cloud's Generative AI Offerings35%- Generative AI application development platforms
- Model Garden and available models
- Overview of Google Cloud generative AI services and tools
- Enterprise integration and security features
- Vertex AI generative AI capabilities
Techniques to Improve Generative AI Model Output20%- Mitigation of bias and inaccuracies
- Prompt engineering principles and best practices
- Evaluation and optimization of output quality
- Fine-tuning and adaptation methods
Business Strategies for Successful Generative AI Solutions15%- Planning and adoption frameworks
- Scaling and measuring success of generative AI initiatives
- Identifying business use cases and value opportunities
- Governance, risk management, and compliance

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A pass requires Not publicly disclosed, and registration costs USD 99 (plus tax where applicable). Every retake bills that fee again, which is why candidates prepare thoroughly with verified PracticeMaterial material before booking their seat.
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Follow the official Google Cloud Certified - Generative AI Leader Exam (Generative-AI-Leader日本語版) weights:
  • Fundamentals of Generative AI (30%)
  • Techniques to Improve Generative AI Model Output (20%)
  • Google Cloud's Generative AI Offerings (35%)
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Generative AI Leader Training Course Generative AI Leader Study Guide An official course builds theory in a structured way, while the PracticeMaterial engine and verified question bank provide the timed rehearsal — together they cover preparation from both directions.

Google Cloud Certified - Generative AI Leader Exam (Generative-AI-Leader日本語版) Sample Questions:

Question #1

ある組織は、顧客サポートの初期問い合わせを自動化し、ウェブサイトやアプリでよくある質問に即座に回答することで、顧客サービスの可用性を向上させ、日常的な問題に対応するライブエージェントチームの作業負荷を軽減したいと考えています。彼らは、顧客の問い合わせを自然で魅力的な方法で理解し、回答できるソリューションを必要としており、ルールベースのロジックと生成型AI機能の両方のオプションを備えたソリューションを求めています。Googleのカスタマーエンゲージメントスイートのどのコンポーネントを使用すべきでしょうか?

  • A. 会話型インサイト
  • B. 対話型エージェント
  • C. Google Cloud Contact Center as a Service
  • D. エージェントアシスト
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #2

ある組織が、従業員の出張予約のための生成型AIエージェントを構築しています。このエージェントは、空室状況、料金、予約状況を確認するために、外部のフライトおよびホテルシステムに接続する必要があります。Google Cloudの推奨プラクティスに従い、エージェントが外部の旅行プロバイダーシステムと連携するための最もシンプルで効果的な方法を実装しようとしています。どのような方法を使用すべきでしょうか?

  • A. 旅行予約機能を追加するプラグイン
  • B. 旅行APIと連携するためのエージェント内の機能
  • C. フライト情報とホテル情報がプリロードされたデータストア
  • D. 旅行APIとの標準化されたエージェントインタラクションのための拡張機能
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #3

膨大な商品カタログと多数のサポートドキュメントを抱える大手eコマース企業では、顧客がウェブサイト上で必要な情報を見つけるのに苦労しています。これは、サポートコストの高騰とユーザーエクスペリエンスの低下につながっています。同社は、ウェブサイトの検索性を向上させ、サポートコストを削減しつつ顧客満足度を高めるために、Google Cloudソリューションの導入を検討しています。同社はどのGoogle Cloud製品を使用すべきでしょうか?

  • A. Google検索
  • B. 頂点AI検索
  • C. Googleショッピング
  • D. Vertex AI Platform
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #4

地理的に分散したチームを抱える大規模な多国籍企業は、知識のサイロ化や重要な社内情報へのアクセスの一貫性の欠如に苦慮しています。このような状況において、Gemini Enterpriseを利用する主なビジネス上のメリットは何でしょうか?

  • A. 社内通信におけるデータ暗号化とコンプライアンスの強化。
  • B. オフィス全体におけるITインフラ管理の改善。
  • C. AIを用いた従業員業績評価の自動化。
  • D. 社内システム間でのシームレスな知識共有とコラボレーション。
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #5

ある世界的なニュース会社は、自社ウェブサイトに掲載するニュース記事の要約を、大規模な言語モデルを用いて自動生成しています。ある国際サミットに関するこのモデルの要約は、実際には発生していない詳細を述べるという幻覚症状が出るまでは正確でした。この会社は、この幻覚症状をどのように克服すべきでしょうか?

  • A. より多様な出力を促進するために、モデルの温度設定を上げます。
  • B. より大規模なニュース記事のデータセットでモデルを微調整します。
  • C. グラウンディングを使用して、モデル出力をソース記事に基づいて決定します。
  • D. 物議を醸す可能性のあるトピックを除外するために、より厳格な安全設定を実装します。
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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