John Davis
회원 가입일: 2015
회원 가입일: 2015
Welcome Gamers! Create and test a prompt, create a conversation, and explore the prompt gallery, all while having fun! Explore Generative AI Studio in Vertex AI. 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.
초급 Prepare Data for ML APIs on Google Cloud 기술 배지를 완료하여 Dataprep by Trifacta로 데이터 정리, Dataflow에서 데이터 파이프라인 실행, Dataproc에서 클러스터 생성 및 Apache Spark 작업 실행, Cloud Natural Language API, Google Cloud Speech-to-Text API, Video Intelligence API를 포함한 ML API 호출과 관련된 기술 역량을 입증하세요. 기술 배지는 Google Cloud 제품 및 서비스 숙련도에 따라 Google Cloud에서 독점적으로 발급하는 디지털 배지로, 기술 배지 과정을 통해 대화형 실습 환경에서 지식을 적용하는 역량을 테스트할 수 있습니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크에 공유할 수 있는 기술 배지를 받을 수 있습니다.
‘시작하기 - 클라우드 리소스 만들기 및 관리하기’ 후에 완료할 실습을 찾고 있는 초보 클라우드 개발자라면 이 퀘스트가 안성맞춤입니다. Cloud Storage 및 Stackdriver와 Cloud Functions와 같은 핵심 애플리케이션 서비스를 자세히 살펴보는 실습을 통해 실무 경험을 쌓게 됩니다. 이 퀘스트를 완료하고 나면 어떤 Google Cloud 이니셔티브에도 적용할 수 있는 유용한 기술을 얻을 수 있습니다. 마지막에 제시되는 챌린지 실습을 포함해 이 퀘스트를 완료하면 특별한 Google Cloud 디지털 배지가 주어집니다. 1분 정도의 동영상을 통해 실습의 주요 개념을 알아볼 수 있습니다.
In this quest you will use several tools available in Google Cloud to manipulate data and create a Google Map - map location details to find subway stations or a business; use geocoding and Apps Script to send an email of a map; visualize data on a customized map; and build a server-side proxy to create a map on a mobile device.
This Quest 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.
중급 Deploy Kubernetes Applications on Google Cloud 기술 배지 과정을 완료하여 Docker 컨테이너 이미지 구성 및 빌드, Google Kubernetes Engine(GKE) 클러스터 생성 및 관리, kubectl을 활용한 효율적인 클러스터 관리, 강력한 지속적 배포(CD) 관행으로 Kubernetes 애플리케이션 배포를 위한 기술을 갖추었음을 입증하세요. 기술 배지는 개인의 Google Cloud 제품 및 서비스 능력에 따라 Google Cloud에서만 독점적으로 발급되는 디지털 배지로, 대화형 실습 환경을 통해 지식을 적용하는 역량을 테스트합니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크와 공유할 수 있는 기술 배지를 받을 수 있습니다.
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.
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.
Earn the introductory skill badge by completing the Build a Website on Google Cloud course. This course is based on the series Get Cooking in Cloud, where you learn how to: Deploy a website on Cloud Run; Host a web app on Compute Engine; Create, deploy, and scale your website on Google Kubernetes Engine; Migrate from a monolithic application to a microservices architecture using Cloud Build. 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.
Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
Welcome, gamers! Since they emerged in 2009, cryptocurrencies have experienced their share of volatility, and are a continual source of fascination. Get a better understanding of cryptocurrency with the labs in this week's game.
입문 Implement Load Balancing on Compute Engine 기술 배지 과정을 완료하여 gcloud 명령어 작성 및 Cloud Shell 사용, Compute Engine에서 가상 머신 만들기 및 배포, 네트워크 및 HTTP 부하 분산기 구성에 관한 본인의 기술을 입증하세요. 기술 배지는 Google Cloud 제품 및 서비스에 대한 개인의 숙련도를 인정하기 위해 Google Cloud에서 단독 발급하는 디지털 배지로서 대화형 실습 환경을 통해 지식을 적용하는 역량을 테스트합니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크에 공유할 수 있는 기술 배지를 받게 됩니다.
Machine Learning is one of the most innovative fields in technology, 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 advanced-level quest, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on GCP.
The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with Google Cloud.
TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
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.
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.
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.
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.
Learn how you can migrate and modernize your workloads on Google's global, secure, and reliable infrastructure. Not sure how to choose the best path to the cloud for your company? Get hands-on experience with the console and see what works for you in these labs. Our goal is to help you take advantage of GCP's high performance computing, to turn your bold ideas into big discoveries with cost-effective, scalable infrastructure.
In this quest, you’ll learn to work with services related to Compute and Networking, including Amazon EC2, Amazon Elastic Load Balancing, and Amazon Virtual Private Cloud (VPC).
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.
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.
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 quest 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! 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.
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 quest, 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.
This advanced-level quest is unique amongst the other catalog 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 Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. 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 the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
Welcome, gamers! Build your own data transformation pipeline that outputs results into BigQuery, all while winning points (and prizes!) in today's Qwiklabs game. Start taking the game lab to score points. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with the lab to get the maximum points. You can take each lab up to 5 times. Winners, collect your prizes at the front of the room!
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 quest, 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? 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.
Welcome, gamers! Use the Google merch store's ecommerce dataset to run typical queries that businesses would want to know about customer purchasing habits, all while winning points (and prizes!) in today's Qwiklabs game. Start taking the game lab to score points. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with the lab to get the maximum points. You can take each lab up to 5 times. Winners, collect your prizes at the front of the room!
Welcome, gamers! Over a billion: that's how many Google Assistant devices will be out in the world by the end of the year. Want in? Learn to build your own Google Assistant app and win points in today's Qwiklabs game. Start taking the game lab to score points. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with the lab to get the maximum points. You can take each lab up to 5 times. Winners, collect your prizes at the front of the room!
This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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.
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 AI Platform. Want extra help? 1-minute videos walk you through key concepts for each lab.
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.
강사가 1일 동안 직접 강의하는 본 강좌는 수강생들에게 도커 컨테이너에서의 작업, 해당 작업을 Google Kubernetes Engine에서 제공하는 쿠버네티스 클러스터로 배포하는 방법 및 증가한 트래픽에 대처할 수 있게 스케일링 하는 방법에 대해 다룹니다. 수강생은 또한 애플리케이션 업데이트에 따라 지속적으로 쿠버네티스 클러스터로 새로운 코드를 배포하는 방법에 대해서 배우게 됩니다
가장 인기 있는 이 탐구 과정에서 Google Cloud를 처음으로 실습할 수 있습니다. Stackdriver 및 Kubernetes의 고급 개념으로 실습하여 VM 가동, 키 인프라 도구 구성과 같은 기본사항을 익혀 보세요.
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.