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

Topic	Details
Topic 1	Business Strategies for a Successful Generative AI Solution: This section of the exam measures the skills of Cloud Architects and evaluates the ability to design, implement, and manage enterprise-level generative AI solutions. It covers the decision-making process for selecting the right solution, integrating AI into an organization, and measuring business impact. A strong emphasis is placed on secure AI practices, highlighting Google’s Secure AI Framework and cloud security tools, as well as the importance of responsible AI, including fairness, transparency, privacy, and accountability.
Topic 2	Techniques to Improve Generative AI Model Output: This section of the exam measures the skills of AI Engineers and focuses on improving model reliability and performance. It introduces best practices to address common foundation model limitations such as bias, hallucinations, and data dependency, using methods like retrieval-augmented generation, prompt engineering, and human-in-the-loop systems. Candidates are also tested on different prompting techniques, grounding approaches, and the ability to configure model settings such as temperature and token count to optimize results.
Topic 3	Fundamentals of Generative AI: This section of the exam measures the skills of AI Engineers and focuses on the foundational concepts of generative AI. It covers the basics of artificial intelligence, natural language processing, machine learning approaches, and the role of foundation models. Candidates are expected to understand the machine learning lifecycle, data quality, and the use of structured and unstructured data. The section also evaluates knowledge of business use cases such as text, image, code, and video generation, along with the ability to identify when and how to select the right model for specific organizational needs.
Topic 4	Google Cloud’s Generative AI Offerings: This section of the exam measures the skills of Cloud Architects and highlights Google Cloud’s strengths in generative AI. It emphasizes Google’s AI-first approach, enterprise-ready platform, and open ecosystem. Candidates will learn about Google’s AI infrastructure, including TPUs, GPUs, and data centers, and how the platform provides secure, scalable, and privacy-conscious solutions. The section also explores prebuilt AI tools such as Gemini, Workspace integrations, and Agentspace, while demonstrating how these offerings enhance customer experience and empower developers to build with Vertex AI, RAG capabilities, and agent tooling.

Reference: https://cloud.google.com/developers/generative-ai-leader

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

Question #1

生成 AI 企業としての Google Cloud の特徴は何ですか?

A. Google Cloud は、すべての生成 AI モデルとデータが完全に保護され、外部ネットワークから分離されていることを保証します。
B. Google Cloud は、継続的なアップデートとプラットフォーム全体の幅広い統合によりイノベーションを可能にする AI ファーストに重点を置いています。
C. Google Cloud は、セキュリティ上のメリットを最大限に高めるために、独自のクローズドソース AI テクノロジーを活用しています。
D. Google Cloud は、構成や管理のオーバーヘッドを必要としない、完全に自律的な AI エージェントを提供します。

Reveal Solution Discussion 0

Correct Answer: B 🗳️