Time Limit
90 minutes
Passing Score
70%
Question Bank
57+
Exam Domains
This exam covers 8 domains with 32 competencies. Each domain is weighted to reflect its importance on the actual exam.
1
Fundamentals of Generative AI
This domain covers the core concepts and principles of generative AI.
0.3%
Weight
5 Competencies
- Exploring Large Language Models (LLMs)
- Understanding Core Generative AI Concepts
- Model Capabilities and Limitations
- Foundation Models and Their Applications
- Prompt Engineering Techniques
2
Google Cloud's Generative AI Offerings
Focuses on Google Cloud's tools and services for generative AI solutions.
0.35%
Weight
5 Competencies
- Utilizing Vertex AI for Generative AI
- Understanding Model Garden and Generative AI Studio
- Exploring Prebuilt Generative AI Applications
- Overview of Google Cloud's AI Platform
- Integrating Generative AI with Google Cloud Services
3
Techniques to Improve Generative AI Model Output
Addresses strategies to enhance the performance of generative AI models.
0.2%
Weight
5 Competencies
- Applying Grounding Techniques
- Fine-Tuning Models for Specific Tasks
- Evaluating Model Performance
- Addressing Model Limitations
- Implementing Effective Prompt Engineering
4
Business Strategies for a Successful Generative AI Solution
Focus on strategic considerations for implementing AI solutions.
0.15%
Weight
5 Competencies
- Measuring AI Impact and ROI
- Ensuring Responsible AI Practices
- Managing AI Governance and Compliance
- Driving Organizational Change with AI
- Developing an AI Adoption Strategy
D1
Fundamentals of Generative AI
Understanding core concepts, terminology, and principles of generative AI.
0.3%
Weight
3 Competencies
- Understand Generative AI Concepts
- Terminology and Key Principles
- Generative AI Model Types
D2
Google Cloud’s Generative AI Offerings
Familiarity with tools, services, and real-world use cases provided by Google Cloud.
0.35%
Weight
3 Competencies
- Google Cloud AI Product Portfolio
- Real-World Use Cases
- Integration and Deployment
D3
Techniques to Improve Generative AI Model Output
Knowledge of prompting, fine-tuning, and large language model (LLM) optimization strategies.
0.2%
Weight
3 Competencies
- Model Fine-Tuning
- Optimization Strategies
- Prompt Engineering
D4
Business Strategies for a Successful Gen AI Solution
Recognizing Google-recommended practices for a secure, responsible, and transformational generative AI solution.
0.15%
Weight
3 Competencies
- AI Governance and Ethics
- Strategic Implementation
- Risk Management
How to Prepare
ProctorPulse uses AI to generate original practice questions aligned with the official Google Cloud exam blueprint.
1
Study the Domains
Review the exam domains and competencies to understand what you need to know.
2
Practice Questions
Take practice exams with 57+ questions covering every domain and competency.
3
Track & Improve
Review explanations, track your scores, and focus on weak areas until you are ready.
