Working with Notebooks in Vertex AI
Earned sept. 1, 2025 EDT
Prepare Data for ML APIs on Google Cloud
Earned sept. 1, 2025 EDT
Introduction to Vertex AI Studio
Earned août 3, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned août 3, 2025 EDT
Professional Machine Learning Engineer Study Guide
Earned juin 8, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned juin 6, 2025 EDT
Gen AI Apps: Transform Your Work
Earned juin 4, 2025 EDT
Gen AI: Navigate the Landscape
Earned juin 2, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned mai 22, 2025 EDT
Gen AI: Beyond the Chatbot
Earned mai 20, 2025 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned fév. 5, 2025 EST
Introduction to Responsible AI
Earned fév. 5, 2025 EST
Generative AI for Business Leaders
Earned jan. 26, 2025 EST
Accelerate Knowledge Exchange with Google Agentspace
Earned jan. 24, 2025 EST
Delivery Shadowing
Earned déc. 26, 2024 EST
Case Studies
Earned déc. 26, 2024 EST
Technology + Beyond the UI
Earned déc. 26, 2024 EST
Technology + Within the UI
Earned sept. 29, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned juil. 27, 2024 EDT
Table Calculations, Pivots, and Visualizations
Earned juin 22, 2024 EDT
Building Reports in Looker
Earned juin 22, 2024 EDT
Liquid Templates and Parameters
Earned juin 22, 2024 EDT
Extends to Keep LookML DRY
Earned juin 11, 2024 EDT
Admin Roles and Folder Access
Earned juin 11, 2024 EDT
Version Control and Caching
Earned juin 5, 2024 EDT
The Modern Data Platform and LookML
Earned mai 23, 2024 EDT
Driving Data Culture and Designing Dashboards
Earned mai 17, 2024 EDT
Achieving Business Outcomes with Looker
Earned mai 16, 2024 EDT
Looker Explained
Earned mai 16, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned mai 6, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned avr. 7, 2024 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned fév. 1, 2024 EST
Essential Google Cloud Infrastructure: Core Services
Earned jan. 10, 2024 EST
Essential Google Cloud Infrastructure: Foundation
Earned jan. 3, 2024 EST
Google Cloud Fundamentals: Core Infrastructure
Earned déc. 27, 2023 EST
This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
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This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.
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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.
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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.
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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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Unite Google’s expertise in search and AI with Google Agentspace, an enterprise tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Google Agentspace assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds.
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In this course, you shadow a series of client meetings led by a Looker Professional Services Consultant.
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By the end of this course, you should feel confident employing technical concepts to fulfill business requirements and be familiar with common complex design patterns.
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In this course you will discover additional tools for your toolbox for working with complex deployments, building robust solutions, and delivering even more value.
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Develop technical skills beyond LookML along with basic administration for optimizing Looker instances
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
En savoir plus
This course reviews the processes for creating table calculations, pivots and visualizations
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This course is designed for Looker users who want to create their own ad-hoc reports. It assumes experience of everything covered in our Get Started with Looker course (logging in, finding Looks & dashboards, adjusting filters, and sending data)
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In this course you will discover Liquid, the templating language invented by Shopify and explore how it can be used in Looker to create dynamic links, content, formatting, and more.
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Hands on course covering the main uses of extends and the three primary LookML objects extends are used on as well as some advanced usage of extends.
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This course is designed to teach you about roles, permission sets and model sets. These are areas that are used together to manage what users can do and what they can see in Looker.
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This course aims to introduce you to the basic concepts of Git: what it is and how it's used in Looker. You will also develop an in-depth knowledge of the caching process on the Looker platform, such as why they are used and why they work
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This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.
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This course provides an iterative approach to plan, build, launch, and grow a modern, scalable, mature analytics ecosystem and data culture in an organization that consistently achieves established business outcomes. Users will also learn how to design and build a useful, easy-to-use dashboard in Looker. It assumes experience with everything covered in our Getting Started with Looker and Building Reports in Looker courses.
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In this course, we’ll show you how organizations are aligning their BI strategy to most effectively achieve business outcomes with Looker. We'll follow four iterative steps: Plan, Build, Launch, Grow, and provide resources to take into your own services delivery to build Looker with the goal of achieving business outcomes.
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By the end of this course, you should be able to articulate Looker's value propositions and what makes it different from other analytics tools in the market. You should also be able to explain how Looker works, and explain the standard components of successful service delivery.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.
En savoir plus
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.
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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
Working with Notebooks in Vertex AI
Earned sept. 1, 2025 EDT
Prepare Data for ML APIs on Google Cloud
Earned sept. 1, 2025 EDT
Introduction to Vertex AI Studio
Earned août 3, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned août 3, 2025 EDT
Professional Machine Learning Engineer Study Guide
Earned juin 8, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned juin 6, 2025 EDT
Gen AI Apps: Transform Your Work
Earned juin 4, 2025 EDT
Gen AI: Navigate the Landscape
Earned juin 2, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned mai 22, 2025 EDT
Gen AI: Beyond the Chatbot
Earned mai 20, 2025 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned fév. 5, 2025 EST
Introduction to Responsible AI
Earned fév. 5, 2025 EST
Generative AI for Business Leaders
Earned jan. 26, 2025 EST
Accelerate Knowledge Exchange with Google Agentspace
Earned jan. 24, 2025 EST
Delivery Shadowing
Earned déc. 26, 2024 EST
Case Studies
Earned déc. 26, 2024 EST
Technology + Beyond the UI
Earned déc. 26, 2024 EST
Technology + Within the UI
Earned sept. 29, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned juil. 27, 2024 EDT
Table Calculations, Pivots, and Visualizations
Earned juin 22, 2024 EDT
Building Reports in Looker
Earned juin 22, 2024 EDT
Liquid Templates and Parameters
Earned juin 22, 2024 EDT
Extends to Keep LookML DRY
Earned juin 11, 2024 EDT
Admin Roles and Folder Access
Earned juin 11, 2024 EDT
Version Control and Caching
Earned juin 5, 2024 EDT
The Modern Data Platform and LookML
Earned mai 23, 2024 EDT
Driving Data Culture and Designing Dashboards
Earned mai 17, 2024 EDT
Achieving Business Outcomes with Looker
Earned mai 16, 2024 EDT
Looker Explained
Earned mai 16, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned mai 6, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned avr. 7, 2024 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned fév. 1, 2024 EST
Essential Google Cloud Infrastructure: Core Services
Earned jan. 10, 2024 EST
Essential Google Cloud Infrastructure: Foundation
Earned jan. 3, 2024 EST
Google Cloud Fundamentals: Core Infrastructure
Earned déc. 27, 2023 EST