Preparing for your Professional Data Engineer Journey
Earned sept. 22, 2025 EDT
Recommendations with AI Applications
Earned août 18, 2025 EDT
Vertex AI Search and Google Agentspace Analytics
Earned août 18, 2025 EDT
Vertex AI Search and Google Agentspace UI Configurations
Earned août 18, 2025 EDT
Create Data Stores for Gen AI Applications
Earned août 18, 2025 EDT
Introduction to AI Applications
Earned août 18, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned juil. 11, 2025 EDT
Implement RAG with Vertex AI
Earned juin 27, 2025 EDT
Gen AI: Navigate the Landscape
Earned mai 16, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned mai 15, 2025 EDT
Gen AI: Beyond the Chatbot
Earned mai 15, 2025 EDT
Looker Studio Pro Essentials
Earned avr. 29, 2025 EDT
Introduction to Data Analytics in Google Cloud
Earned avr. 15, 2025 EDT
Building Codeless Pipelines on Cloud Data Fusion
Earned sept. 3, 2024 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned août 23, 2024 EDT
Essential Google Cloud Infrastructure: Core Services
Earned août 20, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned août 19, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned août 15, 2024 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned août 14, 2024 EDT
Vector Search and Embeddings
Earned août 8, 2024 EDT
Implementing Generative AI with Vertex AI
Earned août 7, 2024 EDT
Create Image Captioning Models
Earned août 7, 2024 EDT
Transformer Models and BERT Model
Earned août 7, 2024 EDT
Encoder-Decoder Architecture
Earned août 7, 2024 EDT
Attention Mechanism
Earned août 7, 2024 EDT
Introduction to Image Generation
Earned août 7, 2024 EDT
Customer Engagement Suite with Google AI Architecture
Earned juil. 12, 2024 EDT
Scaling with Google Cloud Operations
Earned juil. 10, 2024 EDT
DEPRECATED Build LangChain Applications using Vertex AI
Earned juil. 7, 2024 EDT
Trust and Security with Google Cloud
Earned juil. 2, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned juil. 2, 2024 EDT
Exploring Data Transformation with Google Cloud
Earned juil. 2, 2024 EDT
Digital Transformation with Google Cloud
Earned juil. 2, 2024 EDT
Selling the Platform & Building Client Trust
Earned juin 28, 2024 EDT
Generative AI Fundamentals
Earned juin 27, 2024 EDT
Text Prompt Engineering Techniques
Earned juin 27, 2024 EDT
Prompt Design in Vertex AI
Earned juin 26, 2024 EDT
Unlocking the Power of Google Cloud Generative AI for Partners
Earned juin 26, 2024 EDT
Intro to CCAI and CCAI Engagement Framework
Earned juin 26, 2024 EDT
Introduction to Vertex AI Studio
Earned juin 25, 2024 EDT
Generative AI for Business Leaders
Earned juin 25, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned juin 25, 2024 EDT
Configure and Maintain CCAIP as an Admin
Earned juin 24, 2024 EDT
Manage Functions and Reporting with CCAIP
Earned juin 24, 2024 EDT
Handle Consumer Interactions with CCAIP
Earned juin 21, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned juin 4, 2024 EDT
Introduction to Responsible AI
Earned juin 4, 2024 EDT
BI Reporting: Looker Visualization on BigQuery
Earned juin 3, 2024 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned jan. 9, 2024 EST
Introduction to Large Language Models
Earned jan. 8, 2024 EST
Introduction to Generative AI
Earned jan. 8, 2024 EST
Data Warehousing for Partners: Design in BigQuery
Earned jan. 8, 2024 EST
Cloudera to Google Cloud
Earned jan. 7, 2024 EST
Migrating Hadoop Workloads
Earned déc. 10, 2023 EST
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
Do you want to keep your users engaged by suggesting content they'll love?
This course equips you with the skills to build a cutting-edge recommendations app using your own data with no prior machine learning knowledge. You learn to leverage AI Applications to build recommendation applications so that audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives.
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AI Applications provides built-in analytics for your Vertex AI Search and Google Agentspace apps. Learn what metrics are tracked and how to view them in this course.
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Initial deployment of Vertex AI Search and Google Agentspace apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience.
In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Google Agentspace apps.
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Data stores represent a simple way to make content available to many types of generative AI applications, including search applications, recommendations engines, Google Agentspace apps, Agent Development Kit agents, and apps built with Google Gen AI or LangChain SDKs. Connect data from many sources include Cloud Storage, Google Drive, chat apps, mail apps, ticketing systems, third-party file storage providers, Salesforce, and many more.
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This course introduces AI Applications. You will learn about the types of apps that you can create using AI Applications, the high-level steps that its data stores automate for you, and what advanced features can be enabled for Search apps.
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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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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.
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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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This course goes beyond the basics of Looker Studio to explore the powerful features and capabilities of Looker Studio Pro. Learn how to leverage team workspaces for efficient collaboration, enhance data security and administration, and utilize Google Cloud Customer Care for support. Discover premium features that elevate your data visualization and reporting capabilities. This course is designed for users who already have a foundational understanding of Looker Studio and want to unlock its full potential for their business or organization.
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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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This quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.
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Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.
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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, 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.
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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.
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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task.
Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Complete the introductory Build LangChain Applications using Vertex AI skill badge to learn how to build Generative AI applications using LangChain and the Retrieval Augmented Generation (RAG) technique for text-based content, powered by Vertex AI's advanced Generative AI capabilities. Discover how to integrate powerful large language models (LLMs) with search and retrieval workflows, boosting the accuracy and relevance of your generated content. Earn a Google Cloud skill badge and showcase your expertise by completing the course and its final assessment challenge lab.
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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences.
“Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities, learn to identify high-impact use cases, and develop the skills to demonstrate and integrate these technologies seamlessly into client solutions and operations.
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities and learn to identify high-impact use cases.
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This is a introductory course to all solutions in the Contact Centre AI (CCAI) portfolio and the Generative AI features that are poised to transform them. The course also explores the CCAI go to market and engagement model, the business case around CCAI, as well as the use cases and user personas addressed by the solution.
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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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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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Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
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Configure and Maintain CCAIP as an Admin is a course that provides end users with essential learning about the core features, functionality, reporting, and configuration information most relevant to the role. This course is most appropriate for those who perform administrative functions to support the operation of the contact center as well as analyze, troubleshoot, and configure the platform to best meet the demands of customers. While this program will review some monitoring and reporting aspects, those topics are explored in depth in the course titled, “Managing Functions and Reporting with CCAIP.”
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Manage Functions and Reporting with CCAI Platform provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCAI Platform.
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This course teaches contact center agents about the core agent features and functionality in Contact Center AI Platform (CCAIP). CCAIP is a unified contact center platform that accelerates an organization's ability to leverage and deploy CCAI without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.
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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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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.
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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from five products hosted on Cloudera or Hortonworks to corresponding Google Cloud services and hosted products. The migration solutions addressed will be:
HDFS data to Google Cloud Dataproc and Cloud Storage
Hive data to Cloud Dataproc and the Cloud Dataproc Metastore
Hive data to Google Cloud BigQuery
Impala data to Google Cloud BigQuery
HBase to Google Cloud Bigtable
Sample data will be used during all five migrations. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners understanding of the topics.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating workloads from Hadoop environments to corresponding Google Cloud services and hosted products. The following will addressed will be: The Hadoop ecosystem and products Hadoop architecture and post migration architectures to Google Cloud Assessment Data transfer options Workload migrations, namely: Spark to Dataproc Serverless, Apache Oozie to Composer (Airflow), and Hive to BigQuery Security and governance Logging and Monitoring
Preparing for your Professional Data Engineer Journey
Earned sept. 22, 2025 EDT
Recommendations with AI Applications
Earned août 18, 2025 EDT
Vertex AI Search and Google Agentspace Analytics
Earned août 18, 2025 EDT
Vertex AI Search and Google Agentspace UI Configurations
Earned août 18, 2025 EDT
Create Data Stores for Gen AI Applications
Earned août 18, 2025 EDT
Introduction to AI Applications
Earned août 18, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned juil. 11, 2025 EDT
Implement RAG with Vertex AI
Earned juin 27, 2025 EDT
Gen AI: Navigate the Landscape
Earned mai 16, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned mai 15, 2025 EDT
Gen AI: Beyond the Chatbot
Earned mai 15, 2025 EDT
Looker Studio Pro Essentials
Earned avr. 29, 2025 EDT
Introduction to Data Analytics in Google Cloud
Earned avr. 15, 2025 EDT
Building Codeless Pipelines on Cloud Data Fusion
Earned sept. 3, 2024 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned août 23, 2024 EDT
Essential Google Cloud Infrastructure: Core Services
Earned août 20, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned août 19, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned août 15, 2024 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned août 14, 2024 EDT
Vector Search and Embeddings
Earned août 8, 2024 EDT
Implementing Generative AI with Vertex AI
Earned août 7, 2024 EDT
Create Image Captioning Models
Earned août 7, 2024 EDT
Transformer Models and BERT Model
Earned août 7, 2024 EDT
Encoder-Decoder Architecture
Earned août 7, 2024 EDT
Attention Mechanism
Earned août 7, 2024 EDT
Introduction to Image Generation
Earned août 7, 2024 EDT
Customer Engagement Suite with Google AI Architecture
Earned juil. 12, 2024 EDT
Scaling with Google Cloud Operations
Earned juil. 10, 2024 EDT
DEPRECATED Build LangChain Applications using Vertex AI
Earned juil. 7, 2024 EDT
Trust and Security with Google Cloud
Earned juil. 2, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned juil. 2, 2024 EDT
Exploring Data Transformation with Google Cloud
Earned juil. 2, 2024 EDT
Digital Transformation with Google Cloud
Earned juil. 2, 2024 EDT
Selling the Platform & Building Client Trust
Earned juin 28, 2024 EDT
Generative AI Fundamentals
Earned juin 27, 2024 EDT
Text Prompt Engineering Techniques
Earned juin 27, 2024 EDT
Prompt Design in Vertex AI
Earned juin 26, 2024 EDT
Unlocking the Power of Google Cloud Generative AI for Partners
Earned juin 26, 2024 EDT
Intro to CCAI and CCAI Engagement Framework
Earned juin 26, 2024 EDT
Introduction to Vertex AI Studio
Earned juin 25, 2024 EDT
Generative AI for Business Leaders
Earned juin 25, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned juin 25, 2024 EDT
Configure and Maintain CCAIP as an Admin
Earned juin 24, 2024 EDT
Manage Functions and Reporting with CCAIP
Earned juin 24, 2024 EDT
Handle Consumer Interactions with CCAIP
Earned juin 21, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned juin 4, 2024 EDT
Introduction to Responsible AI
Earned juin 4, 2024 EDT
BI Reporting: Looker Visualization on BigQuery
Earned juin 3, 2024 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned jan. 9, 2024 EST
Introduction to Large Language Models
Earned jan. 8, 2024 EST
Introduction to Generative AI
Earned jan. 8, 2024 EST
Data Warehousing for Partners: Design in BigQuery
Earned jan. 8, 2024 EST
Cloudera to Google Cloud
Earned jan. 7, 2024 EST
Migrating Hadoop Workloads
Earned déc. 10, 2023 EST