Reliable Google Cloud Infrastructure: Design and Process - Bahasa Indonesia
Earned Mar 25, 2023 EDT
Scaling with Google Cloud Operations
Earned Des 12, 2022 EST
Modernize Infrastructure and Applications with Google Cloud
Earned Des 12, 2022 EST
Exploring Data Transformation with Google Cloud
Earned Des 12, 2022 EST
Digital Transformation with Google Cloud
Earned Des 12, 2022 EST
Managing Security in Google Cloud
Earned Des 6, 2022 EST
Deploy to Kubernetes in Google Cloud
Earned Des 3, 2022 EST
Build Infrastructure with Terraform on Google Cloud
Earned Des 3, 2022 EST
Set up and Configure a Cloud Environment in Google Cloud
Earned Des 3, 2022 EST
Implement Load Balancing on Compute Engine
Earned Des 1, 2022 EST
Build a Secure Google Cloud Network
Earned Des 1, 2022 EST
Implement Cloud Security Fundamentals on Google Cloud
Earned Nov 30, 2022 EST
Mitigating Security Vulnerabilities on Google Cloud
Earned Nov 30, 2022 EST
Site Reliability Engineering: Measuring and Managing Reliability
Earned Nov 29, 2022 EST
Networking in Google Cloud: Defining and Implementing Networks
Earned Nov 9, 2022 EST
Elastic Google Cloud Infrastructure: Scaling and Automation - Bahasa Indonesia
Earned Nov 5, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Nov 4, 2022 EDT
Exploring APIs
Earned Nov 3, 2022 EDT
Using the Cloud SDK Command Line
Earned Nov 3, 2022 EDT
Perform Foundational Infrastructure Tasks in Google Cloud
Earned Nov 3, 2022 EDT
Google Cloud Essentials
Earned Nov 3, 2022 EDT
Essential Google Cloud Infrastructure: Core Services - Bahasa Indonesia
Earned Nov 1, 2022 EDT
Architecting with Google Kubernetes Engine: Foundations
Earned Okt 31, 2022 EDT
Essential Google Cloud Infrastructure: Foundation - Bahasa Indonesia
Earned Sep 15, 2022 EDT
Google Cloud Fundamentals: Core Infrastructure - Bahasa Indonesia
Earned Sep 10, 2022 EDT
Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions with Vertex AI course, where you will learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models. This skill badge course is for professional Data Scientists and Machine Learning Engineers. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.
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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing.
The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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Earn the intermediate skill badge by completing the Classify Images with TensorFlow on Google Cloud course where you will learn how to use TensorFlow and Vertex AI to create and train machine learning models. You will primarily interact with Vertex AI Workbench user-managed notebooks. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.
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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
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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. 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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Selesaikan badge keahlian pengantar Prepare Data for ML APIs on 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. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud s ebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan kursus badge keahlian ini dan challenge lab penilaian akhir, untuk menerima badge keahlian yang dapat Anda bagikan dengan jaringan Anda.
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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
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Selesaikan badge keahlian tingkat menengah Engineer Data for Predictive Modeling with BigQuery ML untuk menunjukkan keterampilan Anda dalam hal berikut: membangun pipeline transformasi data ke BigQuery dengan Dataprep by Trifacta; menggunakan Cloud Storage, Dataflow, dan BigQuery untuk membangun alur kerja ekstrak, transformasi, dan pemuatan (ETL); membangun model machine learning menggunakan BigQuery ML; dan menggunakan Cloud Composer untuk menyalin data di berbagai lokasi. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan kursus badge keahlian dan challenge lab penilaian akhir untuk menerima badge digital yang dapat Anda bagikan ke jaringan Anda.
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Selesaikan badge keahlian tingkat menengah Create ML Models with BigQuery ML untuk menunjukkan keterampilan dalam hal berikut ini: membuat dan mengevaluasi model machine learning dengan BigQuery ML untuk membuat prediksi data. Badge keahlian merupakan badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan kursus badge keahlian ini, dan challenge lab penilaian akhir, untuk menerima badge keahlian yang dapat Anda bagikan ke jaringan Anda.
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Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge 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. 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 the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network. For practice with BigQuery fundamentals (including working with the console and command line), complete the course titled BigQuery Basics for Data Analysts.
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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
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Selesaikan badge keahlian pengantar Derive Insights from BigQuery Data 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. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan kursus badge keahlian ini dan penilaian akhir challenge lab untuk menerima badge keahlian yang dapat Anda bagikan dengan jaringan Anda.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Bigtable for analysis. Learners get hands-on experience building streaming data pipeline components on Google Cloud by using QwikLabs.
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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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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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Migration from MySQL to Cloud Spanner using Dataflow that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.
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Welcome Gamers! Test your skills and learn BigQuery, all while having fun!
You will compete to see who can finish the game with the highest score.
Earn the 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.
All players will be awarded the game badge.
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Kursus ini memperkenalkan Vertex AI Studio, sebuah alat untuk membuat prototipe dan menyesuaikan model AI generatif. Melalui materi yang imersif, demo yang menarik, dan lab interaktif, Anda akan mengeksplorasi alur kerja AI generatif dan mempelajari cara memanfaatkan Vertex AI Studio untuk aplikasi multimodal Gemini, desain perintah, dan penyesuaian model. Tujuannya adalah agar Anda dapat memanfaatkan potensi model tersebut dalam project dengan Vertex AI Studio.
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Welcome Gamers! Today's game is all about experimenting with Big Query for Machine Learning! Use real life case studies to learn various concepts of BQML and have fun. Take labs to earn points. The faster you complete the lab objectives, the higher your score.
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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 advanced-level quest, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional Challenge Lab at the end of the Deploy to Kubernetes in Google Cloud Quest to receive an exclusive Google Cloud digital badge.
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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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Kursus ini menjelaskan cara membuat model keterangan gambar menggunakan deep learning. Anda akan belajar tentang berbagai komponen model keterangan gambar, seperti encoder dan decoder, serta cara melatih dan mengevaluasi model. Pada akhir kursus ini, Anda akan dapat membuat model keterangan gambar Anda sendiri dan menggunakannya untuk menghasilkan teks bagi gambar.
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Kursus ini memperkenalkan Anda pada arsitektur Transformer dan model Representasi Encoder Dua Arah dari Transformer (Bidirectional Encoder Representations from Transformers atau BERT). Anda akan belajar tentang komponen utama arsitektur Transformer, seperti mekanisme self-attention, dan cara penggunaannya untuk membangun model BERT. Anda juga akan belajar tentang berbagai tugas yang dapat memanfaatkan BERT, seperti klasifikasi teks, menjawab pertanyaan, dan inferensi natural language. Kursus ini diperkirakan memakan waktu sekitar 45 menit untuk menyelesaikannya.
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Kursus ini memberi Anda sinopsis tentang arsitektur encoder-decoder, yang merupakan arsitektur machine learning yang canggih dan umum untuk tugas urutan-ke-urutan seperti terjemahan mesin, ringkasan teks, dan tanya jawab. Anda akan belajar tentang komponen utama arsitektur encoder-decoder serta cara melatih dan menyalurkan model ini. Dalam panduan lab yang sesuai, Anda akan membuat kode pada penerapan simpel arsitektur encoder-decoder di TensorFlow untuk pembuatan puisi dari awal.
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Dalam kursus ini Anda akan diperkenalkan dengan mekanisme atensi, yakni teknik efektif yang membuat jaringan neural berfokus pada bagian tertentu urutan input. Anda akan mempelajari cara kerja atensi, cara penggunaannya untuk meningkatkan performa berbagai tugas machine learning, termasuk terjemahan mesin, peringkasan teks, dan menjawab pertanyaan.
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Kursus ini memperkenalkan model difusi, yaitu kelompok model machine learning yang belakangan ini menunjukkan potensinya dalam ranah pembuatan gambar. Model difusi mengambil inspirasi dari fisika, khususnya termodinamika. Dalam beberapa tahun terakhir, model difusi menjadi populer baik di dunia industri maupun penelitian. Model difusi mendasari banyak alat dan model pembuatan gambar yang canggih di Google Cloud. Kursus ini memperkenalkan Anda pada teori yang melandasi model difusi dan cara melatih serta men-deploy-nya di Vertex AI.
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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 Gen AI 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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Quest level dasar ini berbeda dari penawaran Qwiklabs lainnya. Lab-lab di dalamnya telah diseleksi guna membekali profesional IT dengan praktik langsung tentang berbagai topik dan layanan yang diujikan dalam Sertifikasi Cloud Certified Professional Cloud Architect. Quest ini berisi lab-lab khusus yang akan menguji pengetahuan Anda seputar Google Cloud, mulai dari IAM, networking, hingga deployment Kubernetes Engine. Selesaikan quest ini, termasuk challenge lab di akhir quest, untuk menerima badge digital eksklusif dari Google Cloud. Harap diketahui, meskipun praktik dengan lab ini dapat meningkatkan keterampilan dan kemampuan Anda, sebaiknya pelajari juga panduan ujian serta referensi persiapan lain yang tersedia.
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Complete the intermediate Optimize Costs for Google Kubernetes Engine skill badge to demonstrate skills in the following: creating and managing multi-tenant clusters, monitoring resource usage by namespace, configuring cluster and pod autoscaling for efficiency, setting up load balancing for optimal resource distribution, and implementing liveness and readiness probes to ensure application health and cost-effectiveness. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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This course teaches participants techniques for monitoring and improving infrastructure and application performance in Google Cloud.
Using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.
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This on-demand course equips students to understand and adopt Istio-based
service-mesh with Anthos for centralized observability, traffic management,
and service-level security.
This is the second course of the Architecting Hybrid Cloud Infrastructure with
Anthos series. After completing this course, learners should continue to the
Hybrid Cloud Multi-Cluster with Anthos course.
Completion of the Architecting with Google Kubernetes Engine path is a
prerequisite for this course.
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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.
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This course helps learners create a study plan for the PCA (Professional Cloud Architect) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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Dapatkan badge keahlian dengan menyelesaikan kursus Cloud Architecture: Design, Implement, and Manage untuk menunjukkan keahlian Anda dalam hal berikut: men-deploy situs yang dapat diakses secara publik menggunakan server web Apache, mengonfigurasi VM Compute Engine menggunakan skrip startup, mengonfigurasi RDP yang aman menggunakan Bastion host Windows dan aturan firewall, membangun dan men-deploy image Docker ke cluster Kubernetes serta kemudian mengupdatenya, membuat instance CloudSQL, dan mengimpor database MySQL. Kursus badge keahlian ini merupakan referensi yang bagus untuk memahami topik yang akan muncul di ujian sertifikasi Professional Cloud Architect Tersertifikasi Google Cloud. Badge keahlian merupakan badge digital eksklusif yang diberikan oleh Google Cloud sebagian pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan kursus badge keahli…
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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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Kursus ini membekali peserta dengan keterampilan untuk membuat solusi yang sangat andal dan efisien di Google Cloud menggunakan pola desain yang telah terbukti. Kursus ini merupakan kelanjutan dari kursus Architecting with Google Compute Engine atau Architecting with Google Kubernetes Engine dan memberikan pengalaman interaktif dengan teknologi yang dibahas dalam kursus tersebut. Melalui kombinasi presentasi, aktivitas desain, dan lab interaktif, peserta akan mempelajari cara menentukan dan menyeimbangkan kebutuhan bisnis dan teknis untuk merancang deployment Google Cloud yang sangat andal, sangat tersedia, aman, dan hemat biaya.
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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.
Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
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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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. 'Modernize Infrastructure and Applications with Google Cloud' explores these challenges and offers solutions to overcome them by using cloud technology.
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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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences.
“Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible.
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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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, Cloud IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls. This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.
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Kubernetes adalah sistem orkestrasi container terpopuler, dan Google Kubernetes Engine khusus dirancang untuk mendukung deployment Kubernetes terkelola di Google Cloud. Dalam quest tingkat lanjut ini, Anda akan mendapatkan praktik langsung mengonfigurasi image Docker, container, dan men-deploy aplikasi Kubernetes Engine yang berjalan sepenuhnya. Quest ini akan mengajarkan keterampilan praktis yang diperlukan untuk mengintegrasi orkestrasi container ke dalam alur kerja Anda. Selesaikan quest ini, termasuk challenge lab di akhir quest, untuk menerima badge digital eksklusif dari Google Cloud. Challenge lab ini tidak menyediakan langkah-langkah preskriptif, tetapi menuntut Anda mem-build solusi dengan panduan minimal, dan akan menguji keterampilan Anda dalam menggunakan teknologi Google Cloud.
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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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Quest level dasar ini berbeda dari penawaran Qwiklabs lainnya. Lab-lab di dalamnya telah diseleksi guna membekali profesional IT dengan praktik langsung tentang berbagai topik dan layanan yang diujikan dalam Sertifikasi Google Cloud Certified Associate Cloud Engineer. Quest ini berisi lab-lab khusus yang akan menguji pengetahuan Anda seputar Google Cloud, mulai dari IAM, networking, hingga deployment Kubernetes Engine. Selesaikan quest ini, termasuk challenge lab di akhir quest, untuk menerima badge digital eksklusif dari Google Cloud. Harap diketahui, meskipun praktik dengan lab ini dapat meningkatkan keterampilan dan kemampuan Anda, sebaiknya pelajari juga panduan ujian serta referensi persiapan lain yang tersedia.
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Selesaikan pengantar badge keahlian Implement Load Balancing on Compute Engine untuk menunjukkan keterampilan berikut ini: menulis perintah gcloud dan menggunakan Cloud Shell, membuat dan men-deploy virtual machine di Compute Engine, serta mengonfigurasi jaringan dan load balancer HTTP. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan yang interaktif. Selesaikan badge keahlian ini, dan penilaian akhir Challenge Lab, untuk menerima badge keahlian yang dapat Anda bagikan dengan jaringan Anda.
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Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud. 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 the skill badge, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Selesaikan badge keahlian tingkat menengah Implement Cloud Security Fundamentals on Google Cloud untuk menunjukkan kemahiran dalam hal berikut: membuat dan menetapkan peran dengan Identity and Access Management (IAM); membuat dan mengelola akun layanan; memungkinkan konektivitas pribadi di seluruh jaringan virtual private cloud (VPC); membatasi akses aplikasi menggunakan Identity-Aware Proxy; mengelola kunci dan data terenkripsi dengan Cloud Key Management Service (KMS); dan membuat cluster Kubernetes pribadi. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan kursus badge keahlian ini dan challenge lab penilaian akhir untuk menerima badge digital yang dapat Anda bagikan ke jaringan Anda.
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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.
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Service level indicators (SLIs) and service level objectives (SLOs) are fundamental tools for measuring and managing reliability. In this course, students learn approaches for devising appropriate SLIs and SLOs and managing reliability through the use of an error budget.
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This self-paced training course gives participants broad study of networking options on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy Google Cloud networking technologies, such as Google Cloud Virtual Private Cloud (VPC) networks, subnets and firewalls. The course also covers access control to networks, sharing networks and load balancing.
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Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud. Melalui kombinasi video materi edukasi, demo, dan lab interaktif, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk membuat interkoneksi jaringan yang aman, load balancing, penskalaan otomatis, otomatisasi infrastruktur, serta layanan terkelola.
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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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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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For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
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Jika Anda adalah developer cloud pemula yang menginginkan praktik langsung di luar Getting Started - Create and Manage Cloud Resources, artinya quest ini cocok untuk Anda. Anda akan mendapatkan pengalaman praktik melalui lab yang mendalami Cloud Storage dan layanan aplikasi utama lainnya, seperti Stackdriver dan Cloud Functions. Dengan mengambil quest ini, Anda dapat mengembangkan kemampuan berharga yang dapat diterapkan di semua inisiatif Google Cloud. Selesaikan quest ini, termasuk challenge lab di akhir quest, untuk menerima badge digital eksklusif dari Google Cloud. Tersedia video berdurasi 1 menit yang akan membantu Anda memahami konsep utama lab-lab ini.
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Dalam quest level pendahuluan ini, Anda akan mendapatkan praktik langsung dengan aneka fitur dan layanan dasar Google Cloud Platform. Dasar-Dasar GCP adalah Quest pertama yang direkomendasikan bagi peserta kursus Google Cloud—Anda dapat memulai dengan pengetahuan yang minim atau tanpa pengetahuan sama sekali tentang cloud, dan selesai dengan pengalaman praktis yang dapat diterapkan pada project GCP pertama Anda. Mulai dari menulis perintah Cloud Shell dan menerapkan mesin virtual pertama Anda, hingga menjalankan aplikasi di Kubernetes Engine atau dengan load balancing, Dasar-Dasar GCP merupakan pengenalan terbaik pada fitur-fitur dasar platform cloud. Setiap lab disertai video berdurasi 1 menit yang akan memandu Anda memahami berbagai konsep penting.
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Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud, dengan fokus pada Compute Engine. Melalui kombinasi video materi edukasi, demo, dan lab praktis, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk komponen infrastruktur seperti jaringan, sistem, dan layanan aplikasi. Kursus ini juga membahas cara men-deploy solusi praktis termasuk kunci enkripsi yang disediakan pelanggan, pengelolaan keamanan dan akses, kuota dan penagihan, serta pemantauan resource.
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In this course, "Architecting with Google Kubernetes Engine: Foundations," you get a review of the layout and principles of Google Cloud, followed by an introduction to creating and managing software containers and an introduction to the architecture of Kubernetes.
This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine: Workloads course.
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Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud, dengan fokus pada Compute Engine. Melalui kombinasi video materi edukasi, demo, dan lab interaktif, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk komponen infrastruktur seperti jaringan, virtual machine, dan layanan aplikasi. Anda akan mempelajari cara menggunakan Google Cloud melalui konsol dan Cloud Shell. Anda juga akan mempelajari peran arsitek cloud, pendekatan desain infrastruktur, dan konfigurasi networking virtual dengan Virtual Private Cloud (VPC), Project, Jaringan, Subnetwork, alamat IP, Rute, dan Aturan firewall.
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Google Cloud Fundamentals: Core Infrastructure memperkenalkan konsep dan terminologi penting untuk bekerja dengan Google Cloud. Melalui video dan lab interaktif, kursus ini menyajikan dan membandingkan banyak layanan komputasi dan penyimpanan Google Cloud, bersama dengan resource penting dan alat pengelolaan kebijakan.
Build and Deploy Machine Learning Solutions on Vertex AI
Earned Mei 16, 2024 EDT
Generative AI Explorer - Vertex AI
Earned Mei 15, 2024 EDT
Production Machine Learning Systems
Earned Mei 6, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned Mei 6, 2024 EDT
Machine Learning in the Enterprise
Earned Mei 5, 2024 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Mei 5, 2024 EDT
Classify Images with TensorFlow on Google Cloud
Earned Mar 26, 2024 EDT
TensorFlow on Google Cloud
Earned Mar 25, 2024 EDT
Launching into Machine Learning
Earned Mar 22, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned Mar 22, 2024 EDT
BigQuery for Machine Learning
Earned Mar 14, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned Des 4, 2023 EST
Data Lake Modernization on Google Cloud: Cloud Composer
Earned Des 4, 2023 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned Des 4, 2023 EST
Create ML Models with BigQuery ML
Earned Des 4, 2023 EST
Building Batch Data Pipelines on Google Cloud
Earned Des 2, 2023 EST
Build a Data Warehouse with BigQuery
Earned Okt 23, 2023 EDT
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned Okt 23, 2023 EDT
Derive Insights from BigQuery Data
Earned Okt 23, 2023 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Okt 21, 2023 EDT
Building Resilient Streaming Analytics Systems on Google Cloud
Earned Okt 18, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Okt 17, 2023 EDT
Preparing for your Professional Data Engineer Journey
Earned Okt 16, 2023 EDT
MySQL to Cloud Spanner
Earned Jun 26, 2023 EDT
BigQuery for Data Analysis II
Earned Jun 23, 2023 EDT
Introduction to Vertex AI Studio - Bahasa Indonesia
Earned Jun 22, 2023 EDT
Intro to BigQuery: Analytics & Machine Learning
Earned Jun 20, 2023 EDT
Kubernetes in Google Cloud
Earned Jun 19, 2023 EDT
Generative AI Fundamentals - Bahasa Indonesia
Earned Jun 13, 2023 EDT
Create Image Captioning Models - Bahasa Indonesia
Earned Jun 13, 2023 EDT
Transformer Models and BERT Model - Bahasa Indonesia
Earned Jun 13, 2023 EDT
Encoder-Decoder Architecture - Bahasa Indonesia
Earned Jun 3, 2023 EDT
Attention Mechanism - Bahasa Indonesia
Earned Jun 3, 2023 EDT
Introduction to Image Generation - Bahasa Indonesia
Earned Jun 3, 2023 EDT
Introduction to Responsible AI - Bahasa Indonesia
Earned Jun 3, 2023 EDT
Introduction to Large Language Models - Bahasa Indonesia
Earned Jun 3, 2023 EDT
Introduction to Generative AI - Bahasa Indonesia
Earned Jun 3, 2023 EDT
Deploy and Manage Cloud Environments with Google Cloud
Earned Mei 29, 2023 EDT
Optimize Costs for Google Kubernetes Engine
Earned Mei 29, 2023 EDT
Logging and Monitoring in Google Cloud
Earned Mei 16, 2023 EDT
Hybrid Cloud Service Mesh with Anthos
Earned Mei 12, 2023 EDT
Google Cloud Solutions I: Scaling Your Infrastructure
Earned Mei 12, 2023 EDT
Preparing for your Professional Cloud Architect Journey
Earned Apr 26, 2023 EDT
Cloud Architecture: Design, Implement, and Manage
Earned Apr 25, 2023 EDT
Cloud Architecture
Earned Apr 20, 2023 EDT
Reliable Google Cloud Infrastructure: Design and Process - Bahasa Indonesia
Earned Mar 25, 2023 EDT
Scaling with Google Cloud Operations
Earned Des 12, 2022 EST
Modernize Infrastructure and Applications with Google Cloud
Earned Des 12, 2022 EST
Exploring Data Transformation with Google Cloud
Earned Des 12, 2022 EST
Digital Transformation with Google Cloud
Earned Des 12, 2022 EST
Managing Security in Google Cloud
Earned Des 6, 2022 EST
Deploy to Kubernetes in Google Cloud
Earned Des 3, 2022 EST
Build Infrastructure with Terraform on Google Cloud
Earned Des 3, 2022 EST
Set up and Configure a Cloud Environment in Google Cloud
Earned Des 3, 2022 EST
Implement Load Balancing on Compute Engine
Earned Des 1, 2022 EST
Build a Secure Google Cloud Network
Earned Des 1, 2022 EST
Implement Cloud Security Fundamentals on Google Cloud
Earned Nov 30, 2022 EST
Mitigating Security Vulnerabilities on Google Cloud
Earned Nov 30, 2022 EST
Site Reliability Engineering: Measuring and Managing Reliability
Earned Nov 29, 2022 EST
Networking in Google Cloud: Defining and Implementing Networks
Earned Nov 9, 2022 EST
Elastic Google Cloud Infrastructure: Scaling and Automation - Bahasa Indonesia
Earned Nov 5, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Nov 4, 2022 EDT
Exploring APIs
Earned Nov 3, 2022 EDT
Using the Cloud SDK Command Line
Earned Nov 3, 2022 EDT
Perform Foundational Infrastructure Tasks in Google Cloud
Earned Nov 3, 2022 EDT
Google Cloud Essentials
Earned Nov 3, 2022 EDT
Essential Google Cloud Infrastructure: Core Services - Bahasa Indonesia
Earned Nov 1, 2022 EDT
Architecting with Google Kubernetes Engine: Foundations
Earned Okt 31, 2022 EDT
Essential Google Cloud Infrastructure: Foundation - Bahasa Indonesia
Earned Sep 15, 2022 EDT
Google Cloud Fundamentals: Core Infrastructure - Bahasa Indonesia
Earned Sep 10, 2022 EDT