Google Cloud GenAI Leader Certification: Complete Training

Name: Google Cloud GenAI Leader Certification: Complete Training
Rating: 4.3 (104 reviews)

Master Generative AI with Google Cloud. Learn real-world use cases, tools, strategies & get certification-ready.

Created byLuxmi Narayan

Last updated 6/2026

English

What you'll learn

Understand the fundamentals of Generative AI and its business impact.
Learn how AI, Machine Learning, and LLMs power modern AI solutions.
Explore Google Cloud’s GenAI tools like Gemini, and Vertex AI.
Discover real-world GenAI use cases across industries.
Stay ahead with emerging trends, future technologies, and AI leadership skills.
Understand Google’s principles of Responsible AI and governance.
Master strategies for AI adoption and team leadership.
Develop an enterprise-level GenAI transformation roadmap.
Learn prompt engineering basics for effective AI interactions.

Course content

5 sections • 55 lectures • 5h 0m total length

Getting Familiar with Certification & Exam Format2:54
Requesting Your Feedback0:56
Rate and review this Google Cloud GenAI Leader Certification course to help it improve daily; use the top-right corner rating option, and the instructor will reply with a thank-you note.
What We have Covered in This Course5:37
Getting Familiar With Generative AI2:48
Learn what generative AI is, how it can produce text, images, audio, video, and synthetic data, and explore use cases like chatbots, deepfakes, dubbing, and writing emails or resumes.
How Generative Ai Works At High Level4:38
How Generative AI Transforms Organizations4:38
Foundation Models & Large Language Models (LLMs)4:39
Foundation models are large, versatile, multimodal ai models trained on vast data for diverse tasks. Large language models focus on text and power chatbots; Vertex AI enables easy use.
Training vs Inference5:01
Machine Learning Approaches- Supervised, Unsupervised & Reinforcement8:04
Limitations and Challenges in Generative AI6:41
Demo- Seeing Hallucination in Generative AI Tools3:29
The Machine Learning Lifecycle - Getting Familiar5:57
Structured, Unstructured, Labeled, Unlabeled data Quality and Accessability5:27
Why & How To Choose Right AI Model6:04
Google Foundation Models -Gemini, Gemma, Imagen & Veo4:44

Google Cloud’s Vision for Generative AI6:04
Discover Google's vision for generative AI, emphasizing responsible AI, scalability, security, and collaboration, with Vertex AI, Gemini, and Google Workspace integration that enable leaders to deploy AI quickly via APIs.
Overview Of Google Cloud Generative AI Solutions8:32
Google Cloud Infrastructure for AI - TPUs, GPUs, HyperComputer5:06
Getting Familiar With Vertex AI Platform5:55
Google AI Studio Vs. Vertex AI6:55
Portal Walkthrough- Google AI Studio9:23
Portal Walkthrough- Exploring Vertex AI (Agent Platform)5:59
Prebuilt GenAI Applications- Gemini, Gems, Agentspace, NotebookLM5:52
Demo- Working With Gemini Gems7:36
Demo- GenAI (Gemini) in Google Workspace3:44
Customer Experience AI-Vertex AI Search, Conversational Agents, Agent Assist etc7:51
APIs & AI Services- Vision, Speech Translation, Document AI, Video APIs9:29
AI Agents & Tooling- Plugins, Functions, Extensions, Data Stores, APIs6:17
Prebuilt vs Custom Models - Decision making scenarios for enterprise use cases3:03
Mapping Use Cases To Tools- Choosing right Google Tool For Right Scenario4:34

Understanding Prompt Engineering at High Level6:31
Prompting Techniques- Zero, One, Few Shot, Role Based Techniques4:28
Best Practices For Writing A Prompt12:48
Advanced Prompting- Chain-of-Thought, ReAct, Prompt Chaining7:25
Model Controls - Temperature, top-p tokens, output length, safety settings5:12
WalkThrough- Seeing Model Controls in Google AI Studio Console4:15
Understanding Grounding, RAG & their Relationship9:16
Grounding Types- First Party, Third Party & Google Search5:21
Demo- Seeing Grounding with Google Search in Action4:17
Evaluation & Monitoring- KPIs, Drift Detection, Versioning Monitoring5:13

Roadmap for Enterprise Gen AI Transformation5:27
What Leaders Need To Know Before Adopting Generative AI7:06
Leaders should treat generative AI adoption as a flexible, ongoing journey—start small, test tools, and build privacy, copyright, and safety policies while designing tool-agnostic systems.
Defining Metrics & Measuring Success6:14
Define and measure AI metrics to assess success, covering performance, adoption, and business impact; set clear thresholds, monitor regularly, adjust to sustain momentum and celebrate milestones.
Change Management—Bringing AI to Life6:38
Create a clear vision for AI adoption, communicate benefits, provide training and ongoing support, and address resistance through leadership to sustain successful AI-enabled transformation.
The Evolving Role of the AI Leader4:46
Developing AI Talent in Your Organization6:19
Develop ai talent by combining technical skills like data analysis and modeling with governance, ethics, and cross-functional collaboration, while offering training and real projects to sustain talent.
Establishing data privacy and security best practice5:15
Apply data privacy and security best practices for generative ai by following rules like GDPR, planning data collection and retention, ensuring transparency, and conducting a privacy impact assessment before adoption.
Google Secure AI Framework (SAIF) - Quick Revision1:39
Identifying potential biases and discrimination in generative AI Model - Part15:37
Explain what bias in AI is, identify its sources in generative AI—training data, algorithm bias, and predictive bias—and illustrate with examples like face recognition and loan approvals.
Identifying potential biases and discrimination in generative AI Model - Part22:32
Implementing governance frameworks for responsible AI Development4:16
Implement governance frameworks for responsible AI development by creating clear rules, ensuring fairness and transparency, consulting domain experts, involving stakeholders, and training employees to comply with laws such as GDPR.
Designing with guardrails and human oversight4:08
Leading with human-centric values prioritizing transparency and accountability3:12

Requirements

No coding experience needed — this course is for leaders and decision-makers
A basic understanding of cloud computing concepts is helpful
Curiosity to explore how Generative AI can transform businesses
Familiarity with Google Workspace or Google Cloud (not mandatory, but beneficial)
Willingness to lead AI-powered change in your team or organization

Description

Are you ready to lead the future of AI in your organization?

This course is your complete guide to becoming a Google Cloud Generative AI Leader—equipping you with the strategic mindset, practical tools, and real-world knowledge needed to drive innovation using Google's GenAI technologies.

Whether you're a business leader, IT professional, consultant, or cloud enthusiast—this course will help you bridge the gap between AI technology and impactful business outcomes.

What You’ll Learn:

Understand Generative AI, Foundation Models, and Large Language Models (LLMs) in simple terms
Explore Google Cloud’s powerful GenAI tools: Vertex AI, Gemini, Model Garden, and more
Learn real-world GenAI use cases across industries like healthcare, retail, customer service, and finance
Build GenAI-powered workflows and automation using Google Cloud tools
Master Prompt Engineering basics for leaders and non-technical professionals
Lead responsible AI adoption using Google’s Responsible AI principles
Build a practical enterprise transformation roadmap using GenAI
Get ready to lead teams, influence decision-makers, and drive measurable results

Why This Course?

No coding required – Perfect for leaders, strategists, and decision-makers
Created by a seasoned instructor with 15+ years of experience in cloud, automation, and digital transformation
Content aligned with Google Cloud’s latest GenAI innovations and leadership best practices
Includes downloadable checklists, real examples, and a step-by-step leadership roadmap
Helps you become certification-ready and future-proof your leadership role

Who Is This Course For?

Business leaders, consultants, and project managers
Cloud professionals seeking to lead GenAI adoption
Google Workspace or Google Cloud users exploring GenAI
Anyone responsible for driving innovation, strategy, or digital transformation

Tools & Platforms Covered:

Google Gemini, Bard, and Vertex AI
Generative AI Studio & Model Garden
Google Cloud Workflows, APIs & Workspace integrations

By the end of this course, you’ll have a clear vision, practical skills, and the confidence to lead Generative AI adoption using the world-class tools Google Cloud offers.

Enroll now and start your journey to becoming a Certified Google Cloud Generative AI Leader.

Who this course is for:

Business leaders, managers, and decision-makers exploring Generative AI
Cloud professionals who want to lead AI-powered transformation
Google Workspace or Google Cloud users interested in GenAI leadership
IT and operations leads aiming to integrate AI into business workflows
Consultants and strategists looking to upskill in GenAI use cases
Anyone driving innovation, digital transformation, or tech adoption in their organization

Google Cloud GenAI Leader Certification: Complete Training

What you'll learn

Explore related topics

Course content

Fundamentals of Generative AI15 lectures • 1hr 12min

Google Cloud's GenAI Offerings15 lectures • 1hr 36min

Techniques to Improve and Optimize Model Output10 lectures • 1hr 5min

Business Strategies for Successful Gen AI13 lectures • 1hr 3min

Practice Time2 lectures • 4min

Requirements

Description

Who this course is for: