Lin CAO
Member since 2020
Silver League
10000 points
Scaling with Google Cloud Operations
Earned Nis 30, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned Nis 29, 2022 EDT
Managing Cloud Infrastructure with Terraform
Earned Nis 29, 2022 EDT
Deprecated : Managing Machine Learning Projects with Google Cloud
Earned Nis 28, 2022 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned Nis 26, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Nis 25, 2022 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned Nis 24, 2022 EDT
Build a Data Warehouse with BigQuery
Earned Nis 23, 2022 EDT
[Deprecated] Data Science on Google Cloud: Machine Learning
Earned Nis 22, 2022 EDT
Use Machine Learning APIs on Google Cloud
Earned Nis 21, 2022 EDT
Machine Learning APIs
Earned Nis 21, 2022 EDT
[DEPRECATED] - Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Earned Nis 21, 2022 EDT
Temel: Altyapı
Earned Nis 21, 2022 EDT
Develop Serverless Applications on Cloud Run
Earned Nis 19, 2022 EDT
[DEPRECATED] Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned Nis 18, 2022 EDT
Build Infrastructure with Terraform on Google Cloud
Earned Nis 12, 2022 EDT
Understanding LookML in Looker
Earned Kas 12, 2021 EST
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama
Earned Kas 9, 2021 EST
DEPRECATED BigQuery for Marketing Analysts
Earned Kas 8, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Kas 7, 2021 EST
Temel: Veri, Makine Öğrenimi, Yapay Zeka
Earned Kas 7, 2021 EST
BigQuery Verilerinden Analiz Elde Etme
Earned Kas 4, 2021 EDT
BigQuery for Machine Learning
Earned Eki 10, 2020 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Eki 8, 2020 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned Eki 6, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned Eki 5, 2020 EDT
Intro to ML: Language Processing
Earned Eki 1, 2020 EDT
Intro to ML: Image Processing
Earned Eki 1, 2020 EDT
Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. This course explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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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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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.
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Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Find out how you can discover unexpected use cases, recognize the phases of an ML project and considerations within each, and gain confidence to propose a custom ML use case to your team or leadership or translate the requirements to a technical team.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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Many traditional enterprises use legacy systems and apps that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems and investing in new products and services. This course explores these challenges and offers solutions to overcome them by using cloud technology.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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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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This is the second of two courses of hands-on labs 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 second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.
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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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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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Google Cloud Computing Foundations kursunda, bulut bilişimi alanında daha önce çalışmamış veya bu konuda hiç deneyimi olmayan bireylere;
temel bulut kavramları, büyük veri ve makine öğrenimi gibi kavramlar ve Google Cloud’un bu kavramlarla hangi noktada, nasıl birlikte çalıştığı
ayrıntılı bir genel bakışla anlatılır.
Kursun sonunda öğrenciler bulut bilişimi, büyük veri ve makine öğrenimi konularında
fikir yürütüp bazı becerileri pratik olarak sergileyebilecek seviyeye ulaşacaktır.
Bu kurs, Google Cloud Computing Foundations adlı kurs serisinin bir parçasıdır.
Kurslar aşağıdaki sırayla tamamlanmalıdır:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
Bu üçüncü kursta güvenli ağlar oluşturma,…
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Bulut geliştirme konusunda yeniyseniz ve Google Cloud'un Temel Özellikleri kursunun da ötesinde uygulamalı alıştırma yapmak istiyorsanız bu kurs tam size göre. Cloud Storage'ın yanı sıra Monitoring ve Cloud Functions gibi diğer önemli uygulama hizmetlerini ayrıntılı bir şekilde inceleyen laboratuvarlarla uygulamalı deneyim kazanacaksınız. Her türlü Google Cloud girişiminde kullanabileceğiniz değerli beceriler geliştireceksiniz.
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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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Google Cloud Computing Foundations kursunda, bulut bilişimi alanında daha önce çalışmamış veya bu konuda hiç deneyimi olmayan bireylere;
temel bulut kavramları, büyük veri ve makine öğrenimi gibi kavramlar ve Google Cloud’un bu kavramlarla hangi noktada, nasıl birlikte çalıştığı
ayrıntılı bir genel bakışla anlatılır.
Kursun sonunda öğrenciler bulut bilişimi, büyük veri ve makine öğrenimi konularında
fikir yürütüp bazı becerileri pratik olarak sergileyebilecek seviyeye ulaşacaktır.
Bu kurs, Google Cloud Computing Foundations adlı kurs serisinin bir parçasıdır.
Kurslar aşağıdaki sırayla tamamlanmalıdır:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
Bu ikinci kursta Google Cloud'da depol…
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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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In this course, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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Giriş düzeyindeki Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Dataprep by Trifacta ile veri temizleme, Dataflow'da veri ardışık düzenleri çalıştırma, Managed Service for Apache Spark'ta küme oluşturma ve Apache Spark işleri çalıştırma ve makine öğrenimi API'lerini (Cloud Natural Language API, Google Cloud Speech-to-Text API ve Video Intelligence API dahil olmak üzere) çağırma.
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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. 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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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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Büyük veri, makine öğrenimi ve yapay zeka bilişim alanında günümüzün popüler konularıdır. Ancak bu alanlar yüksek uzmanlık gerektirir ve giriş seviyesi eğitim materyalleri zor bulunur. Neyse ki Google Cloud, bu alanlarda kullanıcı dostu hizmetler sunuyor ve bu giriş seviyesi kurs sayesinde BigQuery, Cloud Speech API ve Video Intelligence gibi araçlarla ilk adımlarınızı atmanıza imkan tanıyor.
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Giriş düzeyindeki BigQuery Verilerinden Analiz Elde Etme beceri rozetini alarak şu konulardaki becerilerinizi gösterin: SQL sorguları yazma, herkese açık tabloları sorgulama, örnek verileri BigQuery'ye yükleme, BigQuery'deki sorgu doğrulayıcı ile yaygın söz dizimi sorunlarını giderme ve BigQuery verilerine bağlanarak Data Studio'da rapor oluşturma.
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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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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. 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 this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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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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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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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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