Google Cloud Generative AI Leader Course

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Google Cloud Generative AI Leader Course
Published 10/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English + subtitle | Duration: 3h 6m | Size: 608.7 MB

Prepare for the Gen AI Leader exam: gen AI fundamentals, Gemini, Agent Platform, RAG, strategy, plus a 60-question exam

What you'll learn
Explain gen AI concepts in plain business language: foundation models, LLMs, tokens, embeddings, multimodal and diffusion models, and how they learn
Match business needs to Google Cloud offerings such as Gemini Enterprise, Gemini Notebook, Gemini in Workspace, and Agent Search
Know when to use Agent Platform, Model Garden, AutoML, Agent Studio, Google AI Studio, RAG Engine, and the Agent Development Kit
Improve model output by choosing correctly between prompt engineering, grounding, RAG, fine-tuning, sampling settings, and human in the loop
Plan a gen AI strategy: choose buy, configure, or build, drive adoption, measure impact with baselines, KPIs, and ROI, and control cost
Apply secure and responsible AI with SAIF, IAM, Security Command Center, Model Armor, privacy techniques, fairness, and transparency

Requirements
No technical background or coding experience is required. The exam and this course are designed for business and technical roles alike.
Curiosity about how generative AI creates value in organizations, and a willingness to practice with scenario questions.
A Google account is optional, but trying the Gemini app or Gemini Notebook while you study will make the concepts stick.

Description
This course contains the use of artificial intelligence.

Prepare for the Google Cloud Certified Generative AI Leader exam, and learn to make gen AI decisions you can defend in a boardroom.
Generative AI is now on every leadership agenda, but most of the hard questions aren't technical. Which problem is worth solving first? Should the company buy a ready-made tool, configure one, or build its own? Why is the assistant inventing policies, and is the fix a better prompt, grounding, or tuning? How do you prove the pilot worked, and how do you keep customer data safe? TheGoogle Cloud Generative AI Leader certification tests exactly these decisions, and this course teaches you to make them with confidence.

The course follows the official exam guide domain by domain. You'll learn what each concept and Google Cloud offering is, and more importantly, when it's the right choice and when it isn't. Throughout the course, you'll follow one realistic company,Fernhill Markets, a grocery chain with 140 stores, a delivery app, and about 9,000 customer care contacts a day. You'll see its leadership team pick its first use cases, discover that its data isn't ready, choose prebuilt offerings for staff, build a customer service journey, fix an assistant that made things up, and present a secure, responsible, measured launch plan to the board.

What makes this course different
-Built around the official exam guide. Every teaching section maps to one of the four exam domains, and time is spent in proportion to the domain weights. Google Cloud's gen AI offerings, the largest domain, gets the most time.

-Current product names. Google renamed many services in 2025 and 2026. The course uses the current names, such as Gemini Enterprise Agent Platform, Agent Studio, Agent Search, Gemini Enterprise, and Gemini Notebook, and teaches the older names you'll still see in study material, such as Vertex AI, Agentspace, and NotebookLM.

-Plain business language. No coding is required. Concepts are explained with business examples and clean diagrams, so you can explain them to executives and engineers alike.

-Exam-style reasoning throughout. Nearly every lecture ends with a check-yourself question, and each domain ends with practice scenarios that show how to find the goal and the constraint, and how to eliminate answers that sound right but don't fit.

-Practice included. A quiz after every section, five narrated practice sets with option-by-option explanations, and a full-length, 60-question practice test.

-About 3 hours 7 minutes of focused video (80 lectures), in short lectures with captions.

What you'll learn

Section 1: Welcome and orientation
The exam format, the four domains and their weights, the 2026 product renames you must recognize, a study plan, and an introduction to Fernhill Markets.

Section 2: Domain 1, Core gen AI concepts
- AI, machine learning, deep learning, and gen AI, and how they relate

- Foundation models, LLMs, tokens, transformers, and embeddings

- Multimodal and diffusion models

- Prompts, prompt engineering, and prompt tuning

- Supervised, unsupervised, and reinforcement learning

- The machine learning lifecycle and the Google Cloud tools for each stage

- Gen AI use cases, and choosing a foundation model for a business need

Section 3: Domain 1, Data, the gen AI landscape, and Google's models
- Data quality and accessibility, structured and unstructured data, and labeled and unlabeled data

- The five layers of the gen AI landscape

- Gemini, Gemma, Imagen, and Veo, and when each fits

Section 4: Domain 2, Google Cloud's strengths and prebuilt offerings
- Google's AI-first approach, enterprise-ready platform, open ecosystem, and AI-optimized infrastructure

- Control over your data, and democratizing AI

- The Gemini app and Gems, Gemini Enterprise, Gemini Notebook, and Gemini for Google Workspace and Google Cloud

Section 5: Domain 2, Customer experience, Agent Platform, and agents
- Agent Search and Google Search grounding

- The Customer Engagement Suite: virtual agents, Agent Assist, and conversation insights

- Gemini Enterprise Agent Platform, Model Garden, AutoML, and Agent Studio versus Google AI Studio

- Google Cloud's RAG offerings, from prebuilt to fully custom

- What agents are, agent tooling, pre-built AI APIs, custom agents, and AI at the edge

Section 6: Domain 3, Techniques to improve model output
- Foundation model limitations: hallucinations, knowledge cutoff, bias, and edge cases

- Google's recommended fixes, and when to prompt, ground, tune, or add human review

- Monitoring and managing models over time

- Prompt engineering, chain-of-thought, ReAct, and metaprompting

- Grounding, how RAG works, and sampling parameters such as temperature and top-p

Section 7: Domain 4, Business strategies for gen AI
- Types of gen AI solutions, and the needs and resources that shape them

- Choosing between buy, configure, and build

- Integrating gen AI with a top-down and bottom-up strategy, and managing change

- Measuring impact with baselines, KPIs, and ROI, and understanding what drives cost

- Secure AI across the ML lifecycle, Google's Secure AI Framework (SAIF), and Google Cloud security tools

- Responsible AI: transparency, privacy, anonymization and pseudonymization, bias, fairness, accountability, and explainability

Section 8: Exam readiness
An exam strategy for scenario questions, final reviews of every domain, and five narrated practice sets of ten questions each, with the reasoning behind every option.

Practice that mirrors the exam
Each section ends with a short quiz. The course closes with afull-length, 60-question practice test that follows the official domain weighting and mixes multiple-choice and multiple-select questions. Every question explains each option, names the trap it tests, and links to official Google documentation.

Want more practice? My companion course,Google Cloud Generative AI Leader: 6 Practice Exams 2025, adds 300 more exam-style questions across six full-length practice exams, each with detailed explanations. It's the ideal next step once you've finished this course and want to test your readiness under exam conditions.

How to use this course to pass
-Watch the sections in order. The Fernhill Markets story builds from section to section.

-Answer every check-yourself question before the answer is revealed.

-Take each section quiz right away, and rewatch the related lectures if you score below 75%.

-Pause during the practice sets, commit to an answer, then listen to why each option is right or wrong.

-Take the full practice test under timed conditions in your final week, then read every explanation.

Who this course is for
This course is designed for anyone preparing for the Generative AI Leader certification: managers, executives, product owners, consultants, and sales and pre-sales professionals, as well as technical people who want the business view. No coding or machine learning background is needed.

How the course is built
Lectures are short and focused, typically two to five minutes, so you can study in small blocks. Concept lectures explain what an idea or offering is and when to choose it. Case study lectures apply those choices to Fernhill Markets, and practice-scenario lectures give you exam-style questions with the reasoning behind each answer. All content, examples, and questions are original and checked against the current exam guide and Google Cloud documentation.

About the exam
At the time of recording, the exam has 50 to 60 multiple-choice and multiple-select questions in 90 minutes, costs $99, and is valid for three years. It's offered online or at a test center in several languages, and there are no prerequisites. Exam details can change, so confirm the current format and price on the official Google Cloud certification page before you book.

Enroll now and build the judgment to pass the Generative AI Leader exam and lead gen AI decisions at work.

This course is not affiliated with, endorsed by, or sponsored by Google LLC. Google Cloud, Gemini, and related marks are trademarks of Google LLC.

Who this course is for
Professionals preparing for the Google Cloud Certified Generative AI Leader exam
Managers, executives, and product owners who make decisions about gen AI investments and adoption
Consultants, sales, and pre-sales teams who advise customers on Google Cloud's gen AI offerings
Anyone who wants a structured, non-technical understanding of gen AI and Google Cloud's AI portfolio

Homepage

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