Set Up an App Dev Environment on Google Cloud
Earned Apr 28, 2022 EDT
Baseline: Infrastructure
Earned Apr 28, 2022 EDT
Google Cloud Essentials
Earned Apr 27, 2022 EDT
Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.
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Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.
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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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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 Generative AI App Builder to integrate enterprise-grade generative AI search.
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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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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 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 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 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 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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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. 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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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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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.
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The demand for data skills is growing rapidly, and we want you to get some of that sweet knowledge! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. Data can be used to identify trends, patterns, and insights that can help businesses improve their operations, products, and services - which makes data career paths highly valuable. There are a lot of different aspects to data science, so it's important to start with the basics - and we’ve got you covered. Kickstart your data skills discovery and get hands-on experience in the Arcade, with labs that help you learn and earn your first Google Cloud credential. No experience required.
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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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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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Complete the intermediate Use Functions, Formulas and Charts in Google Sheets skill badge course to demonstrate skills in the following: analyzing data with functions; visualizing data using charts; and searching, validating, formatting, and displaying data.
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Complete the Analyze BigQuery Data in Connected Sheets skill badge to demonstrate that you can use Connected Sheets to access, analyze, visualize, and share billions of rows of BigQuery data from your Google Sheets spreadsheet.
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Description: According to IDC, by 2026, 7 PB of data will be generated per second globally. But what you *do* with the data is what matters. Data is the heart of digital transformation and offers incredible opportunities for organizations to accelerate the most strategic business outcomes, like revenue and productivity. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud's powerful data tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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More than 90% of IT leaders say they're looking to grow their cloud environments in the next several years, yet more than 80% of those same leaders identified a lack of skills as a barrier to growth. This means that tech skills (particularly cloud skills!) are in high demand. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential. No experience required.
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Complete the introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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Welcome Gamers! Explore the power of machine learning by using multiple machine learning APIs together, all while having fun! Translate the text with the Translation API and analyze it with the Natural Language API. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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Welcome Gamers! Learn to navigate that iterative journey efficiently and effectively using Google Cloud's operations tools!, all while having fun! Deploy a Kubernetes cluster along with a service using Terraform. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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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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Is getting Google Cloud Certified on your 2023 to-do list? Pick up a few new data engineer and cloud developer skills, part of each respective learning path. You'll work with TensorFlow, Kubernetes, and more. Then put your new skills to the test to finish out the game! Don't forget to claim your skill badge progress when you're done.
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In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE.
This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.
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In "Architecting with Google Kubernetes Engine- Workloads", you'll embark on a comprehensive journey into cloud-native application development. Throughout the learning experience, you'll explore Kubernetes operations, deployment management, GKE networking, and persistent storage. This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine- Production course.
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"This course, Architecting with Google Kubernetes Engine: Foundations - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Architecting with Google Kubernetes Engine: Foundations". In this course, "Architecting with Google Kubernetes Engine: Foundations," you get a review of the layout and principles of Google Cloud, followed by an introduction to creating and managing software containers and an introduction to the architecture of Kubernetes.
This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine: Workloads course.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model.
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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.
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Earn the introductory skill badge by completing the Build a Website on Google Cloud skill badge course. This course is based on the Get Cooking in Cloud series and covers`:`Deploying a website on Cloud RunHosting a web app on Compute EngineCreating, deploying, and scaling your website on Google Kubernetes EngineMigrating from a monolithic application to a microservices architecture using Cloud Build
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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API and Video Intelligence. Want extra help? 1-minute videos walk you through key concepts for each lab.
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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.
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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.
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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
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In this quest, you will learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. The labs in this quest use simulator code to mimic IOT devices and the learning here should empower you to implement the same streaming pipeline with real world IoT devices.
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Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.
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Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.
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Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google…
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This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
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In this quest you will learn about the four Google Cloud website architectures available to ensure that your website is available and scalable. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional challenge lab at the end of this Build a Website on Google Cloud to receive an exclusive Google Cloud digital badge. This quest is based on the video series Get Cooking in Cloud.
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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.
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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.
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Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. 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 quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.
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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.
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In this course you will learn how you to harness serious Google Cloud power and infrastructure. The hands-on labs will give you use cases and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your Google Cloud projects to the next level.
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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source Repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.
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Learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. These labs will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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This course is most suitable for those working in a technology or finance role who are responsible for managing Google Cloud costs. You’ll learn how to set up a billing account, organize resources, and manage billing access permissions. In the hands-on labs, you'll learn how to view your invoice, track your Google Cloud costs with Billing reports, analyze your billing data with BigQuery or Google Sheets, and create custom billing dashboards with Looker Studio. References made to links in the videos can be accessed in this Additional Resources document.
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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!
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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.
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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.
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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
Build Infrastructure with Terraform on Google Cloud
Earned Nov 28, 2025 EST
Set Up a Google Cloud Network
Earned Nov 21, 2025 EST
Gemini for Security Engineers
Earned Feb 1, 2024 EST
Enterprise Search on Generative AI App Builder
Earned Feb 1, 2024 EST
Introduction to Vertex AI Studio
Earned Jan 29, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned Dec 2, 2023 EST
Create Image Captioning Models
Earned Jun 15, 2023 EDT
Transformer Models and BERT Model
Earned Jun 15, 2023 EDT
Attention Mechanism
Earned Jun 13, 2023 EDT
Encoder-Decoder Architecture
Earned Jun 13, 2023 EDT
Introduction to Image Generation
Earned Jun 13, 2023 EDT
Generative AI Fundamentals
Earned Jun 13, 2023 EDT
Introduction to Responsible AI
Earned Jun 13, 2023 EDT
Analyze Speech and Language with Google APIs
Earned Jun 10, 2023 EDT
Level 1: Data with Google Cloud
Earned Jun 10, 2023 EDT
Get Started with Dataplex
Earned Jun 10, 2023 EDT
Get Started with Looker
Earned Jun 7, 2023 EDT
Introduction to Large Language Models
Earned Jun 5, 2023 EDT
Introduction to Generative AI
Earned Jun 5, 2023 EDT
Use Functions, Formulas, and Charts in Google Sheets
Earned Apr 27, 2023 EDT
Analyze BigQuery Data in Connected Sheets
Earned Apr 27, 2023 EDT
Level 2: Data Exploration with Looker, BigQuery and Sheets
Earned Apr 27, 2023 EDT
Prepare Data for Looker Dashboards and Reports
Earned Apr 23, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Console
Earned Apr 22, 2023 EDT
Level 1: Managing Resources and Data in the Cloud
Earned Apr 22, 2023 EDT
Monitor and Manage Google Cloud Resources
Earned Apr 22, 2023 EDT
ML API Skills
Earned Mar 31, 2023 EDT
Cloud Hero DevOps Skills
Earned Mar 31, 2023 EDT
Cloud Hero Infra Skills
Earned Mar 29, 2023 EDT
Prepare Data for ML APIs on Google Cloud
Earned Feb 26, 2023 EST
Certification Replay [Arcade]
Earned Feb 26, 2023 EST
Architecting with Google Kubernetes Engine: Production
Earned Jul 27, 2022 EDT
Architecting with Google Kubernetes Engine: Workloads
Earned Jul 18, 2022 EDT
Architecting with Google Kubernetes Engine: Foundations - Locales
Earned Jul 12, 2022 EDT
Create ML Models with BigQuery ML
Earned Jul 8, 2022 EDT
BigQuery for Machine Learning
Earned Jul 8, 2022 EDT
Cloud Logging
Earned Jul 8, 2022 EDT
Build a Website on Google Cloud
Earned Jul 7, 2022 EDT
Baseline: Data, ML, AI
Earned Jul 7, 2022 EDT
Use Machine Learning APIs on Google Cloud
Earned Jul 7, 2022 EDT
Build a Data Warehouse with BigQuery
Earned Jul 7, 2022 EDT
Derive Insights from BigQuery Data
Earned Jul 7, 2022 EDT
Scientific Data Processing
Earned Jul 7, 2022 EDT
Machine Learning APIs
Earned Jul 7, 2022 EDT
Intro to ML: Image Processing
Earned Jul 7, 2022 EDT
Intro to ML: Language Processing
Earned Jul 7, 2022 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Jul 7, 2022 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned Jul 7, 2022 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned Jul 7, 2022 EDT
DEPRECATED IoT in the Google Cloud
Earned Jul 6, 2022 EDT
Develop Serverless Applications on Cloud Run
Earned Jul 5, 2022 EDT
Develop Serverless Apps with Firebase
Earned Jul 5, 2022 EDT
Build Apps & Websites with Firebase
Earned Jul 5, 2022 EDT
Google Cloud Run Serverless Workshop
Earned Jul 4, 2022 EDT
Workspace: Add-ons
Earned Jul 3, 2022 EDT
Website on Google Cloud
Earned Jul 3, 2022 EDT
DEPRECATED Exploring APIs
Earned Jul 2, 2022 EDT
Baseline: Deploy & Develop
Earned Jul 2, 2022 EDT
Cloud Development
Earned Jul 2, 2022 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant
Earned Jul 1, 2022 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned Jul 1, 2022 EDT
Google Developer Essentials
Earned Jul 1, 2022 EDT
Monitor and Log with Google Cloud Observability
Earned Jun 30, 2022 EDT
Google Cloud Solutions I: Scaling Your Infrastructure
Earned Jun 24, 2022 EDT
Implement DevOps Workflows in Google Cloud
Earned Jun 23, 2022 EDT
DEPRECATED Google Cloud's Operations Suite
Earned May 12, 2022 EDT
DEPRECATED Cloud Architecture
Earned May 11, 2022 EDT
Understand Your Google Cloud Costs
Earned May 11, 2022 EDT
DevOps Essentials
Earned May 5, 2022 EDT
Develop Your Google Cloud Network
Earned May 4, 2022 EDT
Cloud Engineering
Earned May 4, 2022 EDT
Deploy Kubernetes Applications on Google Cloud
Earned May 3, 2022 EDT
Kubernetes in Google Cloud
Earned May 3, 2022 EDT
Build a Secure Google Cloud Network
Earned May 2, 2022 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned May 2, 2022 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned Apr 28, 2022 EDT
Set Up an App Dev Environment on Google Cloud
Earned Apr 28, 2022 EDT
Baseline: Infrastructure
Earned Apr 28, 2022 EDT
Google Cloud Essentials
Earned Apr 27, 2022 EDT