Infra Foundations - Implementing Least Privilege for Service Accounts
Earned mars 12, 2024 EDT
Infra Foundations - Implementing Private Google Access for VPC Service Controls
Earned mars 8, 2024 EST
Introduction to Generative AI
Earned jan. 22, 2024 EST
Building Batch Data Pipelines on Google Cloud
Earned jan. 11, 2024 EST
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned jan. 3, 2024 EST
Preparing for your Professional Data Engineer Journey
Earned déc. 27, 2023 EST
Preparing for your Professional Cloud Architect Journey
Earned nov. 19, 2022 EST
#GoogleClout Set 6 (5/10)
Earned sept. 11, 2022 EDT
#GoogleClout Set 5 (4/10)
Earned sept. 11, 2022 EDT
#GoogleClout Set 4 (3/10)
Earned sept. 11, 2022 EDT
#GoogleClout Set 3 (2/10)
Earned sept. 10, 2022 EDT
#GoogleClout Set 2, 1/10
Earned sept. 10, 2022 EDT
#GoogleClout Set 1
Earned avr. 16, 2022 EDT
Serverless Data Processing with Dataflow: Foundations
Earned déc. 19, 2021 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned déc. 17, 2021 EST
Work and Play: Healthcare with Google Cloud
Earned mars 7, 2021 EST
Build a Secure Google Cloud Network
Earned déc. 16, 2020 EST
(Previously named Search on Vertex AI Agent Builder)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use Vertex AI Agent Builder to integrate enterprise-grade generative AI search.
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This course introduces Vertex AI Vector Search and describes how it can be used to build a search application with large language model (LLM) APIs for embeddings. The course consists of conceptual lessons on vector search and text embeddings, practical demos on how to build vector search on Vertex AI, and a hands-on lab.
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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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This course introduces Vertex AI Studio, a tool for prototyping and customizing generative AI models. Through immersive lessons, engaging demos, and a hands-on lab, you'll explore the generative AI workflow and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, and model tuning. The aim is to enable you to unlock the potentials of these models 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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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 7 AI principles.
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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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Complete the intermediate Mitigate Threats and Vulnerabilities with Security Command Center skill badge to demonstrate skills in the following: preventing and managing environment threats, identifying and mitigating application vulnerabilities, and responding to security anomalies.
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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.
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Get Anthos Ready. This Google Kubernetes Engine-centric quest of best practice hands-on labs focuses on security at scale when deploying and managing production GKE environments -- specifically role-based access control, hardening, VPC networking, and binary authorization.
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Earn a DRI badge by completing the Application Modernization - GKE multi-cluster multi-region infrastructure quest, where you demonstrate your understanding of GKE Best-practices
GKE Networking, GKE Security, GKE multi-clusters architecture, VPC networking custom networking mode and VPC routing
When you complete this activity, you can earn the badge displayed above! View all the badges you have earned by visiting your profile page.
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Earn a DRI badge by completing the Infra Foundations - Implementing Least Privilege for Service Accounts quest, where you demonstrate your capabilities to manage service accounts, assign IAM roles, setting up and using impersonation and implementing logging sinks that target GCS buckets.
When you complete this activity, you can earn the badge displayed above! View all the badges you have earned by visiting your profile page.
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Earn a DRI badge by completing the Infra Foundations - Implementing Private Google Access for VPC Service Controls quest, where you demonstrate your capabilities implementing VPC networking custom networking mode, Private Google Access, Cloud DNS response policies, VPC routing and Service Controls.
When you complete this activity, you can earn the badge displayed above! View all the badges you have earned by visiting your profile page.
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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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Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
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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.
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This course helps learners create a study plan for the PCA (Professional Cloud Architect) 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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Flex your Google Clout! Each week unlocks a new cloud puzzle. How fast can you find the solution? Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
En savoir plus
Flex your Google Clout! Each week unlocks a new cloud puzzle. How fast can you find the solution? Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
En savoir plus
Flex your Google Clout! Each week unlocks a new cloud puzzle. How fast can you find the solution? Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
En savoir plus
Flex your Google Clout! Each week unlocks a new cloud puzzle. How fast can you find the solution? Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
En savoir plus
Flex your Google Clout! Each day unlocks a new cloud puzzle. Complete all five and you’ll earn the inaugural Google Cloud badge! Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
En savoir plus
Flex your Google Clout! Each day unlocks a new cloud puzzle. Complete all five and you’ll earn the inaugural Google Cloud badge! Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
En savoir plus
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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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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Google Cloud, in partnership with Harvard Global Health Institute, released the COVID-19 Public Forecasts to serve as an additional resource for healthcare, the public sector, and other organizations responding to the pandemic. In this edition of the Work and Play Series, we are going to learn how to use that data to make predictions and visualizations. You’ll get hands-on experience with exactly the same tools being used to help solve complex problems and keep people safe and healthy.
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Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge, and final assessment challenge lab, to receive a digital badge that you can share with your network.
Developing apps with Vertex AI Agent Builder: Search
Earned juin 5, 2024 EDT
Vector Search and Embeddings
Earned juin 5, 2024 EDT
Introduction to Image Generation
Earned mai 21, 2024 EDT
Introduction to Vertex AI Studio
Earned mai 21, 2024 EDT
Generative AI for Business Leaders
Earned mai 15, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned mai 15, 2024 EDT
Introduction to Responsible AI
Earned mai 14, 2024 EDT
Introduction to Large Language Models
Earned mai 14, 2024 EDT
Mitigate Threats and Vulnerabilities with Security Command Center
Earned mai 9, 2024 EDT
Security Best Practices in Google Cloud
Earned mai 7, 2024 EDT
Google Kubernetes Engine Best Practices: Security
Earned mai 3, 2024 EDT
Application Modernization - GKE multi-cluster multi-region infrastructure
Earned avr. 10, 2024 EDT
Infra Foundations - Implementing Least Privilege for Service Accounts
Earned mars 12, 2024 EDT
Infra Foundations - Implementing Private Google Access for VPC Service Controls
Earned mars 8, 2024 EST
Introduction to Generative AI
Earned jan. 22, 2024 EST
Building Batch Data Pipelines on Google Cloud
Earned jan. 11, 2024 EST
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned jan. 3, 2024 EST
Preparing for your Professional Data Engineer Journey
Earned déc. 27, 2023 EST
Preparing for your Professional Cloud Architect Journey
Earned nov. 19, 2022 EST
#GoogleClout Set 6 (5/10)
Earned sept. 11, 2022 EDT
#GoogleClout Set 5 (4/10)
Earned sept. 11, 2022 EDT
#GoogleClout Set 4 (3/10)
Earned sept. 11, 2022 EDT
#GoogleClout Set 3 (2/10)
Earned sept. 10, 2022 EDT
#GoogleClout Set 2, 1/10
Earned sept. 10, 2022 EDT
#GoogleClout Set 1
Earned avr. 16, 2022 EDT
Serverless Data Processing with Dataflow: Foundations
Earned déc. 19, 2021 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned déc. 17, 2021 EST
Work and Play: Healthcare with Google Cloud
Earned mars 7, 2021 EST
Build a Secure Google Cloud Network
Earned déc. 16, 2020 EST