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.
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.
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.
Selesaikan badge keahlian Mengimplementasikan Alur Kerja DevOps di Google Cloud tingkat menengah untuk menunjukkan keterampilan dalam hal berikut: membuat repositori git dengan Cloud Source Repositories, meluncurkan, mengelola, dan menskalakan deployment di Google Kubernetes Engine (GKE), serta merancang pipeline CI/CD yang mengotomatiskan pembangunan dan deployment image container ke GKE.
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.
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.
Selesaikan badge keahlian tingkat menengah Mengembangkan Aplikasi Serverless dengan Firebase untuk menunjukkan keterampilan dalam hal berikut ini: membuat arsitektur dan membangun aplikasi web serverless dengan Firebase, memanfaatkan pengelolaan database Firestore, mengotomatiskan proses deployment menggunakan Cloud Build, dan mengintegrasikan fungsi Asisten Google ke dalam aplikasi.
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.
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.
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.
In this course you will learn how you to harness serious Google Cloud power and infrastructure. The hands-on labs will give you use cases and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your Google Cloud projects to the next level.
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.
Selesaikan badge keahlian pengantar Mengimplementasikan Cloud Load Balancing untuk Compute Engine untuk menunjukkan keterampilan dalam hal berikut: membuat dan men-deploy virtual machine di Compute Engine serta mengonfigurasi load balancer aplikasi dan jaringan.
Dapatkan badge keahlian pengantar dengan menyelesaikan kursus badge keahlian Membangun Situs di Google Cloud. Kursus ini didasarkan pada serial Get Cooking in Cloud dan mencakup:Men-deploy situs di Cloud RunMenghosting aplikasi web di Compute EngineMembuat, men-deploy, dan menskalakan situs Anda di Google Kubernetes EngineBermigrasi dari aplikasi monolitik ke arsitektur microservice menggunakan Cloud Build