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Apply your skills in Google Cloud console

Julia Bartolo

Учасник із 2022

Machine Learning Operations (MLOps) for Generative AI Earned вер. 12, 2024 EDT
Serverless Data Processing with Dataflow: Operations Earned серп. 13, 2024 EDT
Gemini for end-to-end SDLC Earned січ. 18, 2024 EST
Gemini for Security Engineers Earned січ. 18, 2024 EST
Gemini for Network Engineers Earned січ. 18, 2024 EST
Gemini for Application Developers Earned січ. 18, 2024 EST
Gemini for Cloud Architects Earned січ. 18, 2024 EST
Gemini for DevOps Engineers Earned січ. 16, 2024 EST
Gemini for Data Scientists and Analysts Earned січ. 15, 2024 EST
Engineer Data for Predictive Modeling with BigQuery ML Earned бер. 10, 2022 EST
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud Earned бер. 3, 2022 EST

This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC). Duet AI was renamed to Gemini, our next-generation model.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture. Duet AI was renamed to Gemini, our next-generation model.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks. Duet AI was renamed to Gemini, our next-generation model.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow. Duet AI was renamed to Gemini, our next-generation model.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow. Duet AI was renamed to Gemini, our next-generation model.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow. Duet AI was renamed to Gemini, our next-generation model.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows. Duet AI was renamed to Gemini, our next-generation model.

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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.

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Пройдіть вступний кваліфікаційний курс Підготовка даних для інтерфейсів API машинного навчання в Google Cloud, щоб продемонструвати свої навички щодо очистки даних за допомогою сервісу Dataprep by Trifacta, запуску конвеєрів даних у Dataflow, створення кластерів і запуску завдань Apache Spark у Dataproc, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API. Кваліфікаційний значок – це ексклюзивна цифрова відзнака, яка підтверджує, що ви вмієте працювати з продуктами й сервісами Google Cloud і можете застосовувати ці знання в інтерактивному практичному середовищі. Щоб отримати кваліфікаційний значок і показати його колегам, пройдіть цей курс і підсумковий тест.

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