Mohammad Qara
Menjadi anggota sejak 2019
Silver League
2100 poin
VM Migration
Earned Sep 11, 2019 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned Sep 6, 2019 EDT
BigQuery untuk Machine Learning
Earned Agu 18, 2019 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Agu 4, 2019 EDT
DEPRECATED Application Development - Python
Earned Agu 3, 2019 EDT
[DEPRECATED] Data Engineering
Earned Agu 3, 2019 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned Jul 28, 2019 EDT
Cloud Development
Earned Jul 28, 2019 EDT
Machine Learning APIs
Earned Jul 28, 2019 EDT
DEPRECATED Exploring APIs
Earned Jul 28, 2019 EDT
Workspace: Add-ons
Earned Jul 27, 2019 EDT
[DEPRECATED] Deploying Applications
Earned Jul 27, 2019 EDT
Google Developer Essentials
Earned Jul 16, 2019 EDT
Dasar Pengukuran: Infrastruktur
Earned Jul 6, 2019 EDT
Dasar-Dasar Google Workspace
Earned Jul 6, 2019 EDT
Intro to ML: Image Processing
Earned Jul 6, 2019 EDT
Dasar pengukuran: Data, ML, AI
Earned Jun 29, 2019 EDT
Dasar-Dasar Google Cloud
Earned Apr 14, 2019 EDT
Google Cloud’s four step structured Cloud Migration Path Methodology provides a defined and repeatable path for users to follow when migrating and modernizing Virtual Machines. In this quest, you will get hands-on practice with Google’s current solution set for VM assessment, planning, migration, and modernization. You will start by analyzing your lab environment and building assessment reports with CloudPhysics and StratoZone, then build a landing zone within Google Cloud leveraging Terraform’s infrastructure-as-code templates, next you will manually transform a two-tier application into a cloud-native workload running on Kubernetes, and finally, transform a VM workload into Kubernetes with Migrate for Anthos and migrate a VM between cloud environments.
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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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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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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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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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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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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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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.
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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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Google Cloud 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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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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The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with 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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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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Workspace adalah platform aplikasi kolaboratif Google yang dihadirkan melalui Google Cloud. Dalam kursus tingkat pengantar ini, Anda akan melakukan praktik langsung dengan aplikasi inti Workspace dari perspektif pengguna. Meskipun ada lebih banyak aplikasi dan komponen alat di Workspace selain yang dibahas di sini, Anda akan mendapatkan pengalaman menggunakan aplikasi utama: Gmail, Kalender, Spreadsheet, dan beberapa aplikasi lainnya. Setiap lab dapat diselesaikan dalam waktu 10-15 menit, namun disediakan waktu tambahan agar peserta dapat mengeksplorasi aplikasi-aplikasi tersebut secara mandiri dan bebas.
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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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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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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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