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Terapkan keterampilan Anda di Konsol Google Cloud

RITESH PATEL

Menjadi anggota sejak 2020

Silver League

1300 poin
Deployment & Management Earned Des 31, 2020 EST
Serverless Design with AWS Lambda Earned Des 30, 2020 EST
Kubernetes di Google Cloud Earned Des 29, 2020 EST
Advanced Operations Using Amazon Redshift Earned Des 29, 2020 EST
DEPRECATED Creating with Google Maps Earned Jun 7, 2020 EDT
BigQuery untuk Machine Learning Earned Mei 30, 2020 EDT
Cloud Healthcare API Earned Mei 4, 2020 EDT
Machine Learning APIs Earned Apr 19, 2020 EDT
Intro to ML: Image Processing Earned Mar 28, 2020 EDT
Security on AWS Earned Mar 22, 2020 EDT

In this quest, you’ll learn to work with services related to Deployment and Management, including AWS Identity and Access Management (IAM), AWS Elastic Beanstalk, AWS CloudFormation, and AWS OpsWorks.

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In this Quest, you will learn how to write functions with the AWS Lambda Service that respond to events and integrate other AWS Services. You will create applications that write records to Amazon DynamoDB, send messages with Amazon SNS, and monitor events in Amazon CloudWatch and external services. You will even write a back-end function in Lambda for creating a voice-response app for Alexa and the Amazon Echo.

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Kubernetes adalah sistem orkestrasi container paling populer, dan Google Kubernetes Engine dirancang secara khusus untuk mendukung deployment Kubernetes terkelola di Google Cloud. Dalam kursus tingkat lanjut ini, Anda akan mendapatkan praktik langsung dalam mengonfigurasi Image Docker, container, serta men-deploy aplikasi Kubernetes Engine yang sepenuhnya lengkap dan siap produksi. Kursus ini akan mengajari Anda keterampilan praktis yang diperlukan untuk mengintegrasikan orkestrasi container ke dalam alur kerja Anda sendiri. Apakah Anda sedang mencari challenge lab interaktif untuk menunjukkan keterampilan Anda dan menguji pengetahuan yang dimiliki? Setelah menyelesaikan kursus ini, selesaikan Challenge Lab tambahan di akhir kursus Men-deploy Aplikasi Kubernetes di Google Cloud untuk menerima badge digital eksklusif Google Cloud.

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In this Quest, you will delve deeper into the uses and capabilities of Amazon Redshift. You will use a remote SQL client to create and configure tables, and gain practice loading large data sets into Redshift. You will explore the effects of schema variations and compression. You will explore visualization of Redshift data, and connect Redshift with Amazon Machine Learning to create a predictive data model.

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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.

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Ingin membangun model ML dalam hitungan menit, bukan jam, hanya dengan menggunakan SQL? BigQuery ML memperluas akses machine learning dengan memungkinkan analis data membuat, melatih, mengevaluasi, dan memprediksi sesuatu dengan model machine learning menggunakan alat serta keterampilan SQL yang ada. Dalam rangkaian lab ini, Anda akan bereksperimen dengan beragam jenis model dan mempelajari ciri-ciri model yang baik.

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Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By supporting standards-based data formats and protocols of existing healthcare technologies, Cloud Healthcare API connects your data to advanced Google Cloud capabilities, including streaming data processing with Cloud Dataflow, scalable analytics with BigQuery, and machine learning with Cloud Machine Learning Engine. In this Quest you will use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets.

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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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This quest is designed to teach you how to apply AWS Identity and Access Management, in concert with several other AWS Services, to address real-world application and service security management scenarios.

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