How long does it take to complete this training?

The training is approximately 2 hours in duration, providing a focused, high-impact learning experience. Although short, it delivers the essential skills and knowledge necessary for understanding and implementing generative AI solutions within an enterprise context.

Can I preview a course before enrolling?

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

When will I have access to the lectures and assignments?

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

What will I get when I enroll?

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Google Cloud Generative AI Leader Training 2025

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Google Cloud Generative AI Leader Training 2025

Instructor: Packt - Course Instructors

Included with

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6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understand the core concepts of Generative AI, including NLP and large language models.
Explore the machine learning lifecycle and how it relates to responsible AI deployment.
Gain hands-on experience using Google Cloud’s generative AI tools like Vertex AI and Gemini.
Develop strategies to mitigate AI risks, including bias and hallucination, within enterprise applications.

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There are 6 modules in this course

This course features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Embark on a transformative journey with the Google Cloud Generative AI Leader Training, designed to equip you with the essential skills and knowledge to become a certified Generative AI leader. Through engaging lessons, you will understand the fundamental concepts of Generative AI, including the core technologies such as AI, machine learning, and natural language processing (NLP). The course will provide a comprehensive view of how these technologies are applied in real-world scenarios, particularly in Google Cloud’s ecosystem. You will also dive into critical aspects such as prompt engineering, model performance, and data management, with a focus on practical applications. As you progress, the course guides you through the Google Cloud tools and platforms specifically tailored for generative AI. From TPUs to enterprise-ready AI strategies, you will explore scalable AI solutions designed for businesses of all sizes. You will also be introduced to Google's unique AI technologies, including Gemini, Gemma, and Vertex AI. The course is structured to help you master everything from the AI lifecycle to deployment strategies, ensuring you are well-prepared to work with AI at the enterprise level. This course is ideal for those aiming to work with Google Cloud’s generative AI tools or seeking to build expertise in AI governance, security, and scalability. It's designed for learners interested in AI, cloud computing, and enterprise innovation. A background in technology or business is recommended, but there are no strict prerequisites. The course is suitable for intermediate learners seeking to enhance their expertise in the rapidly evolving field of AI. By the end of the course, you will be able to define key generative AI concepts, apply machine learning techniques to real-world problems, leverage Google Cloud tools to scale AI solutions, and integrate responsible AI practices in enterprise environments.

In this module, we will introduce the course structure, objectives, and provide an overview of the certification process. We will also guide you in assessing whether this course is a fit for your background and career aspirations. Lastly, you’ll learn how to navigate and optimize your learning experience throughout the course.

What's included

4 videos1 reading

In this module, we will dive into the fundamental concepts behind Generative AI, including its definitions and key differentiators. You will learn about AI’s core components, such as ML, NLP, and LLMs, while exploring practical business applications. Finally, we’ll cover essential techniques and their use in shaping innovative AI solutions.

What's included

14 videos1 assignment

14 videos Total 26 minutes

What is Generative AI (Generative AI Explained)? Definitions and Differentiators 1 minute
Core Concepts of Generative AI: AI, ML, NLP, LLMs, and Foundation Models 2 minutes
Mastering Prompt Engineering, Diffusion Models, and Multimodal AI 2 minutes
Real-World Business Applications of Generative AI 1 minute
Supervised, Unsupervised, and Reinforcement Learning in Generative AI 2 minutes
The Machine Learning Lifecycle: From Data Ingestion to Responsible Deployment 2 minutes
Google Cloud AI Tools Mapped to the ML Lifecycle 2 minutes
Choosing the Right Foundation Model: Modality, Context, and Cost 2 minutes
Model Performance, Fine-Tuning, and Security in Generative AI 2 minutes
Data Quality and Accessibility: Foundations of Responsible AI 2 minutes
Structured vs. Unstructured Data in Generative AI Workflows 3 minutes
Labeled vs. Unlabeled Data: Choosing the Right Training Strategy 2 minutes
The Gen AI Technology Stack: From Infrastructure to Applications 2 minutes
Gemini, Gemma, Imagen, and Veo: Google's Foundation Models Explained 2 minutes

1 assignment Total 15 minutes

Fundamentals of Generative AI: Concepts, Models, and Business Relevance - Assessment 15 minutes

In this module, we will explore how Google Cloud’s platform stands apart in the Generative AI landscape. You will learn about its unique tools, including the Gemini suite, and how they integrate into business operations. The module will also highlight how Google’s AI solutions provide scalable, secure, and governed AI capabilities for enterprises.

What's included

16 videos1 assignment

16 videos Total 24 minutes

What Sets Google Apart in Generative AI 1 minute
Enterprise-Ready AI: Privacy, Scale, and Reliability on Google Cloud 1 minute
Open, Governed, and Accountable: Google's AI Strategy for Enterprises 1 minute
TPUs, GPUs, and the AI Hypercomputer: Scaling Performance with Google 1 minute
Data Privacy, Model Governance, and Control with Google Cloud AI 1 minute
Gemini App vs. Gemini Advanced: Choosing the Right Enterprise Tool 1 minute
Google Agentspace: Custom Agents, NotebookLM, and Search Integration 1 minute
Gemini for Google Workspace: AI Inside Gmail, Docs, Sheets, and More 1 minute
Vertex AI Search vs. Google Search: Enterprise Knowledge Retrieval 1 minute
Customer Engagement AI: Contact Center, Agent Assist, and Insights 1 minute
Vertex AI, Model Garden, and AutoML: Tools for Every Developer Level 2 minutes
Retrieval-Augmented Generation (RAG): APIs and Enterprise Workflows 2 minutes
Vertex AI Agent Builder: Low-Code Tools for Custom AI Workflows 2 minutes
Extensions, Plugins, and Data Access: Making Agents Actionable 2 minutes
Speech, Vision, Translation, and Document AI: Google Cloud APIs 2 minutes
Google AI Studio vs. Vertex AI Studio: Prototyping vs. Production 2 minutes

1 assignment Total 15 minutes

Google Cloud Gen AI: Platform, Tools, and Enterprise Capabilities - Assessment 15 minutes

In this module, we will focus on the potential risks associated with Generative AI and strategies for mitigating these challenges. You will learn essential techniques like grounding and prompt engineering to ensure responsible AI outputs. We’ll also cover how to monitor and fine-tune AI systems to maintain quality and trustworthiness.

What's included

9 videos1 assignment

9 videos Total 21 minutes

Common Gen AI Risks: Bias, Hallucination & Knowledge Gaps 2 minutes
Mitigation Strategies: Grounding, RAG, HITL & Fine-Tuning 2 minutes
Monitoring Gen AI: KPIs, Observability & Feature Store 2 minutes
Prompt Engineering: Zero-Shot, One-Shot, and Few-Shot Techniques 2 minutes
Role Prompting and Prompt Chaining for Structured AI Behavior 2 minutes
Chain-of-Thought and ReAct Prompting: Reasoning and Action 3 minutes
Grounding in Gen AI: Enterprise, Third-Party, and Public Data 2 minutes
How RAG Improves Output Accuracy, Relevance, and Trust 2 minutes
Tuning Output with Sampling Parameters: Tokens, Temperature, Top-p 3 minutes

1 assignment Total 15 minutes

Responsible Generative AI: Risks, Grounding, and Output Control - Assessment 15 minutes

In this module, we will explore how to map Generative AI solutions to specific business needs and align them with organizational goals. You will gain insights into the integration process, including overcoming common challenges and implementing secure and ethical AI practices. This module also covers measuring the impact of AI on business outcomes.

What's included

9 videos1 assignment

9 videos Total 24 minutes

Mapping Solutions – Text, Image, Code, Personalization 2 minutes
Aligning Solutions with Business Needs 2 minutes
Steps to Integrate Gen AI into the Enterprise 3 minutes
Impact Measurement Techniques 3 minutes
Google's Secure AI Framework (SAIF) 3 minutes
IAM, Secure-by-Design Infrastructure, Monitoring Tools 3 minutes
Transparency, Explainability, and Accountability 2 minutes
Privacy – Anonymization, Pseudonymization 2 minutes
Bias, Fairness, and Ethical Business Use 3 minutes

1 assignment Total 15 minutes

Scaling and Governing Generative AI in the Enterprise - Assessment 15 minutes

In this final module, we will prepare you for the certification exam by reviewing essential topics and providing practice questions. You will gain tips for managing your time during the exam and strategies for avoiding common pitfalls. We will conclude with final tips to help you succeed in the exam and earn your Generative AI Leader certification.

What's included

3 videos3 assignments

Instructor

Packt - Course Instructors

Packt

1,566 Courses 441,543 learners

Offered by

Packt

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Frequently asked questions

Generative AI refers to a category of artificial intelligence that is designed to generate new content, such as text, images, or other data, by learning patterns from existing data. It is highly relevant today as it is transforming industries by enabling machines to create novel and useful outputs. This technology is being applied in areas like content creation, personalized marketing, customer service, and even drug discovery. Mastery of generative AI can help professionals stay competitive in an increasingly AI-driven world.

The Google Cloud Generative AI Leader Training 2025 is an in-depth program that prepares individuals to become certified Generative AI leaders. The training covers fundamental AI concepts, explores Google Cloud’s AI tools, and addresses the practical application of generative AI in real-world business contexts. Participants will learn how to leverage Google Cloud’s infrastructure and AI solutions to create and deploy scalable generative AI applications.

After completing this training, you will be equipped to design and deploy generative AI solutions using Google Cloud's platform. You will also have the skills needed to manage the entire AI lifecycle, from data collection to model deployment. Additionally, you will be prepared to lead generative AI initiatives within an organization, ensuring scalability, security, and ethical use of AI technologies.

The course is designed for professionals with a background in AI, cloud computing, or enterprise innovation. It is ideal for those who already have a basic understanding of machine learning or artificial intelligence concepts, as the training dives into more advanced topics such as prompt engineering, model fine-tuning, and the use of Google Cloud’s AI tools. Familiarity with cloud platforms and AI development would be beneficial, but it is not a strict prerequisite.

This training is intended for professionals who are looking to advance their careers in AI and cloud technologies. It is especially useful for AI engineers, cloud architects, data scientists, and business leaders interested in understanding how generative AI can be integrated into business strategies. Whether you're looking to get certified or simply enhance your knowledge in this field, this program is designed for anyone aiming to take leadership roles in AI-driven projects.