[NEW] Generative AI Leader Certification

About this course

Detailed Exam Domain CoverageTo pass the official Google Cloud Generative AI Leader certification exam, you need to master four specific operational areas. The practice tests in this course are mapped directly to this blueprint:

• Domain 1: Fundamentals of Generative AI (30% of the exam)Distinguishing between predictive machine learning and generative AI paradigms.
• Core AI/ML concepts, neural network foundations, and basic transformer architectures.
• Identifying generative model capabilities, boundaries, and practical technical limitations.
• Standard terminology, training workflows, and foundational lifecycle stages.

Domain 2: Google Cloud’s Generative AI Offerings (35% of the exam)Navigating the Google Cloud AI ecosystem (Vertex AI, Gemini models, and enterprise tools).

Utilizing fully managed Cloud Gen AI APIs and platform features for business applications.

Deploying specialized conversational frameworks, search platforms, and tools like Agentspace.

Mapping enterprise business requirements to specific Google Cloud architectures.

Domain 3: Techniques to Improve GenAI Model Output (20% of the exam)Designing effective prompt engineering strategies (zero-shot, few-shot, and chain-of-thought).

Differentiating between parameter fine-tuning and Retrieval-Augmented Generation (RAG).

Detecting, mitigating, and managing model hallucinations and systemic training biases.

Establishing quantitative and qualitative evaluation metrics for generative outputs.

Domain 4: Business Strategies for a Successful GenAI Solution (15% of the exam)Formulating organizational AI adoption roadmaps, calculating ROI, and determining total cost of ownership (TCO).

Executing ri

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