Google Generative-AI-Leader日本語 Exam Details & Actual Exam Questions
- Exam Code/Number: Generative-AI-Leader日本語
- Exam Name/Title: Google Cloud Certified - Generative AI Leader Exam (Generative-AI-Leader日本語版)
- Certification Provider: Google
- Corresponding Certification: Google Cloud Certified
- Exam Questions: 79
- Updated On: Jul,15 2026
- Certification Level: Foundational
Google Cloud Certified - Generative AI Leader Exam (Generative-AI-Leader日本語版) Exam Questions
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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 |
| Exam Format: | Multiple choice |
| Certificate Validity Period: | 3 years |
| Exam Price: | USD 99 (plus tax where applicable) |
| Exam Duration: | 90 minutes |
| Available Languages: | English, Japanese, Spanish, Portuguese |
| Real Exam Qty: | 50-60 |
| Sample Questions: | Google Generative-AI-Leader日本語 Sample Questions |
| 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:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Google Cloud's Generative AI Offerings | 35% | - Overview of Google Cloud generative AI services and tools - Vertex AI generative AI capabilities - Generative AI application development platforms - Enterprise integration and security features - Model Garden and available models |
| Topic 2: Techniques to Improve Generative AI Model Output | 20% | - Fine-tuning and adaptation methods - Evaluation and optimization of output quality - Prompt engineering principles and best practices - Mitigation of bias and inaccuracies |
| Topic 3: Business Strategies for Successful Generative AI Solutions | 15% | - Planning and adoption frameworks - Governance, risk management, and compliance - Scaling and measuring success of generative AI initiatives - Identifying business use cases and value opportunities |
| Topic 4: Fundamentals of Generative AI | 30% | - Core concepts and characteristics of generative AI - Key technologies and differences from traditional AI - Responsible AI principles and application - Foundation models: definition, capabilities, and use cases |
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