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Lawrence Chow

Учасник із 2019

Бронзова ліга

Кількість балів: 2300
Anthos: Service Mesh Earned вер. 4, 2020 EDT
DEPRECATED Application Development - Python Earned вер. 3, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud Earned вер. 2, 2020 EDT
Use Machine Learning APIs on Google Cloud Earned вер. 1, 2020 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud Earned серп. 31, 2020 EDT
Початок роботи з даними, машинним навчанням і штучним інтелектом Earned серп. 31, 2020 EDT
Google Kubernetes Engine Best Practices Earned вер. 27, 2019 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned вер. 22, 2019 EDT
Cloud Architecture - Design, Implement, and Manage Earned вер. 21, 2019 EDT
Kubernetes in Google Cloud Earned вер. 16, 2019 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned вер. 15, 2019 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned вер. 14, 2019 EDT
Основи Google Cloud Earned вер. 13, 2019 EDT
Cloud Development Earned вер. 8, 2019 EDT
DEPRECATED Cloud Architecture Earned вер. 7, 2019 EDT

This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on GCP. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.

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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.

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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.

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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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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 Managed Service for Apache Spark, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API.

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Зараз усі говорять про масиви даних, машинне навчання й штучний інтелект, але це досить вузькоспеціалізовані теми, про які важко знайти матеріали, зрозумілі не лише спеціалістам. На щастя, Google Cloud пропонує зручні сервіси в цих галузях, а завдяки цьому вступному курсу ви зможете ознайомитися з такими інструментами, як BigQuery, Cloud Speech API і Video Intelligence.

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Get Anthos Ready. Demand for Google Kubernetes Engine is growing, and customers are looking to Google and its partners to provide in-depth technical knowledge. This first Google Kubernetes Engine-centric Quest of best practices hands-on labs will get you started containerizing to modernize in place , and then managing your deployed apps and services -- with monitoring, tracing, and logging.

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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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This quest of "Challenge Labs" gives the student preparing for the Google Cloud Certified Professional Cloud Architect certification hands-on practice with common business/technology solutions using Google Cloud architectures. Challenge Labs do not provide the "cookbook" steps, but require solutions to be built with minimal guidance, across many Google Cloud technologies. All labs have activity tracking, and in order to earn this badge you must score 100% in each lab. This quest is not easy and will put your Google Cloud technology skills to the test! Be aware that while practice with these labs will increase your knowledge and abilities, additional study, experience, and background in cloud architecture is recommended to prepare for this certification. Complete this quest to receive an exclusive Google Cloud digital badge.

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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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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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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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На цьому вступному курсі ви отримаєте практичний досвід роботи з основними інструментами й сервісами Google Cloud. Також вам доступні додаткові відео, які допоможуть краще зрозуміти контекст і закріпити знання щодо тем, розглянутих у практичних заняттях. Google Cloud "Основи" – це рекомендований початковий курс для тих, хто починає вивчати Google Cloud. Ви можете розпочати навчання, маючи мінімальні знання про хмарні технології або взагалі не маючи їх, і отримати практичний досвід, який зможете застосувати у своєму першому хмарному проєкті Google Cloud. "Основи Google Cloud" дають вичерпне уявленні про ключові функції платформи – від написання команд у Cloud Shell і розгортання першої віртуальної машини до запуску додатків на Kubernetes Engine і використання розподілу навантаження.

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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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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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