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Best courses to learn Google Cloud Platform
Integrate Search in Applications using Vertex AI Agent Builder
This is a self-paced lab that takes place in the Google Cloud console. This lab is part of a series designed to provide hands-on experience with Generative AI on Google Cloud.
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Filtering and Sorting Data in Looker
This is a Google Cloud Self-Paced Lab. In this lab, you will learn how to filter and sort data, and create looks with Looker.
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Ingesting New Datasets into BigQuery
This is a self-paced lab that takes place in the Google Cloud console. This lab focuses on how to ingest new datasets into tables inside of BigQuery.
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Google Cloud Pub/Sub: Qwik Start - Command Line
This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to publish and consume messages with a pull subscriber, using the Google Cloud command line. Watch the short video <A HREF="https://youtu.be/oKU2wbTXMTY">Simplify Event Driven Processing with Cloud Pub/Sub</A>.
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Working with Cloud Dataprep on Google Cloud
Cloud Dataprep is Google's self-service data preparation tool. In this lab, you will learn how to use Cloud Dataprep to clean and enrich multiple datasets using a mock use case scenario of customer info and purchase history.
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GKE Workload Optimization
This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates how optimization in your cluster's workloads can lead to an overall optimization of your resources and costs. It walks through a few different workload optimization strategies such as container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets.
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Cloud Functions: Qwik Start - Console
This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to create and deploy a Cloud Function using the Cloud Platform Console. Watch the short video Connect & Extend GCP Services with Google Cloud Functions.
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Building Scalable Java Microservices with Spring Boot and Spring Cloud
"Microservices" describes a software design pattern in which an application is a collection of loosely coupled services. These services are fine-grained, and can be individually maintained and scaled. The microservices architecture is ideal for the public cloud, with its focus on elastic scaling with on-demand resources. In this course, you will learn how to build Java applications using Spring Boot and Spring Cloud on Google Cloud. You'll use Spring Cloud Config to manage your application's configuration. You'll send and receive messages with Pub/Sub and Spring Integration. You'll also use
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Hosting a Web App on Google Cloud Using Compute Engine
This is a self-paced lab that takes place in the Google Cloud console. In this lab you’ll deploy and scale a Web App on Google Compute Engine.
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Designing and Querying Bigtable Schemas
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you explore a Bigtable instance and use the Bigtable CLI (cbt CLI) to query data in Bigtable. You also design a table schema and row key using best practices for Bigtable.
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Use Data Canvas to Visualize and Design Queries
This is a self-paced lab that takes place in the Google Cloud console. In this lab you learn how to use Data Canvas to visualize and design queries.
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Introduction to Controlled Generation with the Gemini API
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will learn how to use the controlled generation capability in the Vertex AI Gemini API.
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Introduction to Image Generation
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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Classify Images of Cats and Dogs using Transfer Learning
This is a self-paced lab that takes place in the Google Cloud console. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. This lab uses transfer learning to train your machine. In transfer learning, when you build a new model to classify your original dataset, you reuse the feature extraction part and re-train the classification part with your dataset. This method uses l
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