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Terapkan keterampilan Anda di Konsol Google Cloud

Ασπασία Λουκέρη

Menjadi anggota sejak 2017

Silver League

15465 poin
Generative AI Fundamentals - Bahasa Indonesia Earned Des 30, 2023 EST
Pengantar Responsible AI Earned Des 30, 2023 EST
Pengantar Model Bahasa Besar Earned Des 30, 2023 EST
Pengantar AI Generatif Earned Des 30, 2023 EST
DEPRECATED Exploring APIs Earned Agu 27, 2021 EDT
Menyiapkan Jaringan Google Cloud Earned Agu 17, 2021 EDT
Data Catalog Fundamentals Earned Agu 16, 2021 EDT
DevOps Essentials Earned Agu 16, 2021 EDT
Menyiapkan Lingkungan Pengembangan Aplikasi di Google Cloud Earned Agu 15, 2021 EDT
Intro to ML: Image Processing Earned Agu 8, 2021 EDT
Menyiapkan Data untuk Dasbor dan Laporan Looker Earned Agu 8, 2021 EDT
Looker Challenge - Part 1 Earned Agu 8, 2021 EDT
Intermediate ML: TensorFlow on Google Cloud Earned Agu 7, 2021 EDT
DEPRECATED Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications Earned Agu 6, 2021 EDT
Pengantar ML: Pemrosesan Bahasa Earned Agu 6, 2021 EDT
Mendapatkan Insight dari Data BigQuery Earned Agu 6, 2021 EDT
Advanced ML: ML Infrastructure Earned Agu 6, 2021 EDT
Google Developer Essentials Earned Agu 6, 2021 EDT
Cloud Engineering Earned Agu 6, 2021 EDT
Membuat Model ML dengan BigQuery ML Earned Agu 6, 2021 EDT
Menyiapkan Data untuk ML API di Google Cloud Earned Agu 6, 2021 EDT
Mission: Predict the Path Earned Agu 6, 2021 EDT
Security on AWS Earned Okt 16, 2020 EDT
DevZone Quest Earned Agu 6, 2019 EDT
BigQuery untuk Machine Learning Earned Agu 6, 2019 EDT
DEPRECATED BigQuery for Marketing Analysts Earned Agu 6, 2019 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Agu 6, 2019 EDT
DEPRECATED BigQuery for Data Warehousing Earned Agu 6, 2019 EDT
Cloud Hero Speedrun: Data Engineering Earned Agu 1, 2019 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned Apr 14, 2019 EDT
OK Google! Speedrun Earned Apr 5, 2019 EDT
DEPRECATED Network Performance and Optimization Earned Apr 4, 2019 EDT
Kubernetes di Google Cloud Earned Mar 26, 2019 EDT
Solutions Architect - Associate Earned Mar 26, 2019 EDT
DEPRECATED Cloud Architecture Earned Mar 26, 2019 EDT
Dasar-Dasar Keamanan & Identitas Earned Mar 22, 2019 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Mar 21, 2019 EDT
DEPRECATED BigQuery for Data Analysis Earned Mar 21, 2019 EDT
Dasar-Dasar Google Cloud Earned Mar 20, 2019 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned Mar 20, 2019 EDT
DEPRECATED Application Development - Python Earned Des 22, 2018 EST
Baseline: Deploy & Develop Earned Des 22, 2018 EST
Dasar Pengukuran: Infrastruktur Earned Des 19, 2018 EST
Deployment & Management Earned Des 10, 2018 EST
Programming Windows on AWS Earned Des 9, 2018 EST
Solutions Architect - Professional Earned Des 9, 2018 EST
Digital Media Earned Des 9, 2018 EST
Storage & CDN Earned Des 9, 2018 EST
DEPRECATED IoT in the Google Cloud Earned Des 9, 2018 EST
Workspace: Add-ons Earned Des 2, 2018 EST
Cloud SQL Earned Des 2, 2018 EST
Machine Learning APIs Earned Des 2, 2018 EST
Compute & Networking Earned Okt 20, 2018 EDT
Websites & Web Apps Earned Okt 20, 2018 EDT
Corporate Apps on AWS for Windows Earned Okt 19, 2018 EDT
Advanced Operations Using Amazon Redshift Earned Okt 19, 2018 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning Earned Okt 18, 2018 EDT
Data Science on Google Cloud: Machine Learning Earned Okt 17, 2018 EDT
Databases on AWS for Windows Earned Okt 15, 2018 EDT
Big Data on AWS Earned Okt 15, 2018 EDT
[DEPRECATED] Data Engineering Earned Okt 12, 2018 EDT
Scientific Data Processing Earned Okt 10, 2018 EDT
Data Science on Google Cloud Earned Okt 6, 2018 EDT
Dasar pengukuran: Data, ML, AI Earned Okt 1, 2018 EDT

Dapatkan badge keahlian dengan menyelesaikan kursus Introduction to Generative AI, Introduction to Large Language Models, dan Introduction to Responsible AI. Dengan berhasil menyelesaikan kuis akhir, Anda membuktikan pemahaman Anda tentang konsep dasar AI generatif. Badge keahlian adalah badge digital yang diberikan oleh Google Cloud sebagai pengakuan atas pengetahuan Anda tentang produk dan layanan Google Cloud. Pamerkan badge keahlian Anda dengan menampilkan profil Anda kepada publik dan menambahkannya ke profil media sosial Anda.

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Ini adalah kursus pengantar pembelajaran mikro yang dimaksudkan untuk menjelaskan responsible AI, alasan pentingnya responsible AI, dan cara Google mengimplementasikan responsible AI dalam produknya. Kursus ini juga memperkenalkan 7 prinsip AI Google.

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Ini adalah kursus pengantar pembelajaran mikro yang membahas definisi model bahasa besar (LLM), kasus penggunaannya, dan cara menggunakan prompt tuning untuk meningkatkan performa LLM. Kursus ini juga membahas beberapa alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.

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Ini adalah kursus pengantar pembelajaran mikro yang bertujuan untuk mendefinisikan AI Generatif, cara penggunaannya, dan perbedaannya dari metode machine learning konvensional. Kursus ini juga mencakup Alat-alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.

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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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Dapatkan badge keahlian dengan menyelesaikan kursus Menyiapkan Jaringan Google Cloud, untuk mempelajari cara menjalankan tugas-tugas networking dasar di Google Cloud Platform, yakni membuat jaringan kustom, menambahkan aturan firewall subnet, lalu membuat VM dan menguji latensi saat VM berkomunikasi satu sama lain.

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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.

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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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Dapatkan badge keahlian dengan menyelesaikan kursus Menyiapkan Lingkungan Pengembangan Aplikasi di Google Cloud, yang memungkinkan Anda mempelajari cara membangun dan menghubungkan infrastruktur cloud yang berpusat pada penyimpanan menggunakan kemampuan dasar teknologi berikut: Cloud Storage, Identity and Access Management, Cloud Functions, dan Pub/Sub.

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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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Selesaikan badge keahlian pengantar Menyiapkan Data untuk Dasbor dan Laporan Looker untuk menunjukkan keterampilan dalam hal berikut: memfilter, mengurutkan, dan melakukan pivot pada data; menggabungkan hasil dari sejumlah Eksplorasi Looker; serta menggunakan fungsi dan operator untuk membangun dasbor dan laporan Looker untuk analisis dan visualisasi data.

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It's time to roll up your sleeves and dig into some data to get hands-on practice in Looker the self-service data analytics platform! Complete every activity AND post a screenshot of your newly minted Skill Badge in the Learning Forum area of the Community (https://bit.ly/gcc-looker1) to earn a special Community Badge. The Community member* at the top of the scoreboard at the time the game is closed will be rewarded with something objectively cool. (*You must be a registered Community member to be included in the running for top dog.)

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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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In this course you will learn how to use several BigQuery ML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, and see how to use BigQuery ML for a classification task that predicts the likelihood of a website visitor making a purchase.

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Bukan rahasia lagi bahwa machine learning adalah salah satu bidang yang berkembang paling cepat di ranah teknologi, dan Google Cloud Platform telah berperan penting dalam memajukan pengembangannya. Dengan berbagai API, GCP memiliki alat untuk hampir semua tugas machine learning. Dalam kursus pengantar ini, Anda akan melakukan praktik langsung dengan machine learning sebagaimana diterapkan pada pemrosesan bahasa, melalui serangkaian lab yang akan memungkinkan Anda mengekstrak entity dari teks, melakukan analisis sentimen dan sintaksis, serta menggunakan Speech to Text API untuk melakukan transkripsi.

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Selesaikan badge keahlian pengantar Mendapatkan Insight dari Data BigQuery untuk menunjukkan keterampilan dalam hal berikut: menulis kueri SQL, membuat kueri tabel publik, memuat sampel data ke dalam BigQuery, memecahkan masalah error sintaksis umum dengan validator kueri di BigQuery, dan membuat laporan di Looker Studio dengan menghubungkannya ke data BigQuery.

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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, 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 at scale and how to employ the advanced ML infrastructure available on Google Cloud.

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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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Kursus pengantar ini unik dibandingkan penawaran kursus lainnya. Semua lab dalam kursus ini telah diseleksi untuk membekali profesional IT dengan praktik langsung terkait berbagai topik dan layanan yang muncul di Sertifikasi Associate Cloud Engineer yang Tersertifikasi Google Cloud. Dari IAM, networking, hingga deployment Kubernetes Engine, kursus ini terdiri atas beberapa lab khusus yang akan menguji pengetahuan Anda terkait Google Cloud. Perlu diketahui bahwa meskipun praktik dalam lab akan meningkatkan keterampilan dan kemampuan Anda, sebaiknya Anda juga meninjau panduan ujian dan referensi persiapan lainnya yang tersedia.

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Selesaikan badge keahlian tingkat menengah Membuat Model ML dengan BigQuery ML untuk menunjukkan keterampilan dalam hal berikut: membuat dan mengevaluasi model machine learning dengan BigQuery ML untuk membuat prediksi data.

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Selesaikan badge keahlian pengantar Menyiapkan Data untuk ML API di Google Cloud untuk menunjukkan keterampilan Anda dalam hal berikut: menghapus data dengan Dataprep by Trifacta, menjalankan pipeline data di Dataflow, membuat cluster dan menjalankan tugas Apache Spark di Dataproc, dan memanggil beberapa ML API, termasuk Cloud Natural Language API, Google Cloud Speech-to-Text API, dan Video Intelligence API.

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Study Jam organizers, welcome to your preview mission! Preview the first global mission with us so you’re prepared to support your communities. Planet Zorg is under threat! An asteroid is hurtling through space, speeding towards our hero’s home. But where will it fall? Help ML-49 predict the future with this mission’s labs. You’ll learn skills like forecasting and prediction, with tools like BigQuery and AI Platform. The more points you score, the better chance you and ML-49 have of predicting the asteroid’s drop zone.

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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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Welcome to DevZone Quest, a set of labs to deepen your understanding of the technology behind the Cloud Showcase Experiments featured in the Google Cloud Next 2019 San Francisco DevZone.

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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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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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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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Start the 30-day challenge strong with a speedrun! Two labs in this game fulfill requirements towards your Data Engineering cert practice badge, and all four get you hands-on experience with key data tools and concepts.

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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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Welcome to the Friday Speedrun, 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 labs one by one 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 each lab to get the maximum points.

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If you want to take your Google Cloud networking skills to the next level, look no further. This course is composed of labs that cover real-life use cases and it will teach you best practices for overcoming common networking bottlenecks. From getting hands-on practice with testing and improving network performance, to integrating high-throughput VPNs and networking tiers, Network Performance and Optimization is an essential course for Google Cloud developers who are looking to double down on application speed and robustness.

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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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Achieving AWS Certification requires hands-on experience. This quest helps you get hands-on practice with several key services as you prepare for the AWS Certified Solutions Architect – Associate Exam. Visit AWS Certification to learn more about this exam and find more resources to prepare.

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Quest level dasar ini berbeda dengan penawaran Qwiklabs lainnya. Semua lab yang termasuk dalam level ini telah diseleksi untuk membekali profesional IT dengan praktik langsung tentang berbagai topik dan layanan yang diujikan dalam Sertifikasi Google Cloud Certified Professional Cloud Architect . Dari IAM, hingga jaringan, dan penerapan Kubernetes Engine, quest ini tersusun atas sejumlah lab spesifik yang akan menguji pengetahuan Anda tentang GCP. Harap diketahui bahwa, meskipun praktik dengan lab ini akan meningkatkan keterampilan dan kemampuan Anda, sebaiknya Anda juga mempelajari panduan ujian serta referensi persiapan lain yang tersedia.

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Keamanan adalah fitur layanan Google Cloud yang tidak dapat dikompromikan, dan Google Cloud telah mengembangkan alat khusus untuk memastikan keamanan dan identitas di seluruh project Anda. Dalam kursus pengantar ini, Anda akan melakukan praktik langsung dengan Layanan Identity and Access Management (IAM) Google Cloud, yang merupakan layanan utama untuk mengelola akun pengguna dan virtual machine. Anda akan mendapatkan pengalaman dengan keamanan jaringan dengan menyediakan VPC dan VPN, serta mempelajari alat-alat yang tersedia untuk mendapatkan perlindungan dari ancaman keamanan dan kebocoran data.

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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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Want to learn the core SQL and visualization skills of a Data Analyst? Interested in how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.

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Dalam kursus tingkat pemula ini, Anda akan mendapatkan praktik langsung dengan alat dan layanan dasar Google Cloud. Video opsional disediakan untuk memberikan konteks dan ulasan lebih lanjut mengenai konsep-konsep yang dibahas dalam lab ini. Dasar-Dasar Google Cloud adalah kursus pertama yang direkomendasikan bagi peserta kursus Google Cloud— Anda bisa mengikutinya dengan pengetahuan yang minim atau tanpa pengetahuan sama sekali tentang cloud, dan mendapatkan pengalaman praktis yang dapat diterapkan pada project Google Cloud pertama Anda setelah menyelesaikan kursus ini. Mulai dari menulis perintah Cloud Shell dan men-deploy virtual machine pertama Anda, hingga menjalankan aplikasi di Kubernetes Engine atau dengan load balancing, Dasar-Dasar Google Cloud merupakan pengantar utama untuk fitur dasar platform ini.

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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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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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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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Jika Anda adalah developer cloud pemula yang mencari praktik langsung di luar Google Cloud Essentials, kursus ini cocok untuk Anda. Anda akan mendapatkan pengalaman praktis melalui lab yang mendalami Cloud Storage dan layanan aplikasi utama lainnya seperti Monitoring dan Cloud Functions. Anda akan mengembangkan keahlian berharga yang dapat diterapkan untuk inisiatif Google Cloud apa pun.

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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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Learn how to develop applications in Microsoft Visual Studio leveraging AWS services.

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Achieving AWS Certification requires hands-on experience. This quest helps you get hands-on practice with several key services as you prepare for the AWS Certified Solutions Architect – Professional Exam. Visit AWS Certification to learn more about this exam and find more resources to prepare.

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AWS provides a set of on-demand storage, archive, transcoding, and streaming services for businesses that are running photo, video, and file storage applications in the cloud. In this quest, you’ll learn to work with advanced services for digital media on AWS.

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In this Quest, you’ll learn to work with services related to Storage and Content Delivery Networks, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), and Amazon CloudFront.

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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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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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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.

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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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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).

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AWS offers services that provide businesses with a flexible, highly scalable, and low-cost way to deliver their websites and web applications. In this quest, you’ll learn to work with foundational services for marketing websites on AWS.

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Learn how to deploy Microsoft Windows Server-based applications in the AWS cloud, including Microsoft Exchange, Dynamics CRM and SharePoint.

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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 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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This is the second of two Quests 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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Learn how to deploy and administer databases running on Microsoft Windows Server in Amazon EC2 and Amazon RDS.

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Scientists, developers, and other technologists from many different industries are taking advantage of AWS to perform big data analytics and meet the challenges of the increasing volume, variety, and velocity of digital information. AWS offers a portfolio of cloud computing services to help you manage big data by reducing costs, scaling to meet demand, and increasing the speed of innovation. In this quest, you’ll learn to work with advanced services for Big Data.

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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.

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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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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.

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Big data, machine learning, dan kecerdasan buatan menjadi topik komputasi yang populer saat ini, tetapi bidang tersebut sangat terspesialisasi dan materi pengantarnya sulit diperoleh. Untungnya, Google Cloud menyediakan layanan yang mudah digunakan dalam bidang tersebut, dan melalui kursus tingkat pengantar ini, Anda dapat mengambil langkah pertama dengan alat seperti BigQuery, Cloud Speech API, dan Video Intelligence.

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