Google Cloud Generative AI Leader – Certification Prep
Course Curriculum
7 modules designed to master the subject.
Module 1: Generative AI Fundamentals
Understand the AI hierarchy, how GenAI works, and common terminology like LLMs and prompt engineering.
Module 2: The Google Cloud Generative AI Ecosystem
Explore the 5 layers of GenAI, Vertex AI Model Garden, Studio, and Agent Builder.
The 5 Layers of Generative AI: From Hardware to Application
Understand the comprehensive Google Cloud stack for GenAI. We dissect the 5 layers: Infrastructure (TPUs), Models (Gemini), Platforms (Vertex AI), Agents, and Applications.
Vertex AI Deep Dive: Model Garden, Studio, and Agent Builder
A tour of the primary tools in Google Cloud for building GenAI apps. Learn how to discover models in the Garden, prototype in the Studio, and build search apps with Agent Builder.
Module 3: Improving Model Value & Accuracy
Master prompt engineering, RAG, grounding, and when to use fine-tuning.
Prompt Engineering for Leaders: Structure, Context, and Iteration
A practical guide to prompt engineering for business leaders. Learn the 4 components of a perfect prompt and iterative strategies to get reliable business outcomes.
Retrieval-Augmented Generation (RAG): Connecting AI to Your Data
The most important acronym in enterprise AI. Learn how RAG solves the knowledge cutoff problem, reduces hallucinations, and connects Gemini to your private PDFs and databases.
Grounding: Anchoring AI in the Real World
Learn how to stop AI from making things up. We explore 'Grounding' in Vertex AI, using Google Search or your own data to verify facts and provide citations.
Fine-Tuning vs. Prompting: The Cost of Customization
The million-dollar decision. Learn when to simply prompt the model (Context Learning) and when to invest in Fine-Tuning. We compare cost, complexity, and performance.
Module 4: Business Strategy & Use Cases
Identify value in creation, summarization, and discovery. Assess ROI and build vs buy decisions.
The 3 Categories of GenAI Value: Creation, Summarization, Discovery
How to find high-value AI use cases. We break down the 3 primary value drivers: Generating new content, compressing information, and finding hidden insights.
Generative AI Agents: From Chatbots to Action Bots
The future of AI is Agentic. Learn how Agents differ from standard LLMs by using 'Tools' to perform tasks like booking appointments, querying SQL databases, and sending emails.
Assessing ROI & Feasibility: The Low-Hanging Fruit Matrix
How to prioritize AI projects. We introduce the Impact/Effort matrix, the Buy vs. Build calculation, and how to spot high-risk, low-reward traps.
Module 5: Responsible AI & Governance
Manage risks, bias, and security using Google's Responsible AI principles and SAIF.
Responsible AI: Principles, Bias, and Safety
AI is powerful but dangerous. Learn Google's 7 AI Principles and how to identify and mitigate bias in your models.
Data Privacy & Governance: Keeping Secrets Secret
The #1 fear of the C-Suite. 'Will Gemini learn from my data?' We answer definitively how Google Cloud isolates your data and the difference between Consumer and Enterprise terms.
Compliance & Regulation: The EU AI Act and Beyond
The legal landscape is changing. Learn about the risk-based approach of the EU AI Act and how to classify your AI projects to stay legal.
Module 6: Exam Preparation Strategy
Review exam format, keywords, and take a mock assessment to ensure readiness.
The Exam: Structure, Registering, and Passing Strategy
Everything you need to know about the 'Google Cloud Generative AI Leader' certification exam. Logistics, question format, and time management.
Practice Exam: 10 Tough Questions
Test your knowledge with 10 high-difficulty scenarios mirroring the actual exam. Covers RAG, Fine-Tuning, Agents, and Responsibility.
Capstone Project: Designing 'TrustBank AI'
Apply everything you've learned. You will design a secure, compliant, RAG-powered GenAI banking assistant. We provide the architecture diagram and the defense strategy.
Capstone Project
Design a comprehensive Generative AI solution for a business problem using Google Cloud tools.
Course Overview
Format
Self-paced reading
Duration
Approx 6-8 hours
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