ALI HAIDER
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This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.
Learn about the fundamental features of Security Command Center on Google Cloud. Spend time in this course to understand assets, detection and compliance. Security Command Center is a key part of your Google Cloud security journey, complete these modules and quiz to earn a completion badge.
This course provides a comprehensive overview of Google Cloud Security Command Center (SCC) Enterprise, a Cloud-Native Application Protection Platform (CNAPP) solution that helps organizations prevent, detect, and respond to threats across Google Cloud services. You will learn about core SCC Enterprise features, including enhanced threat detection, in-depth vulnerability management, and integrated case management. Fundamental concepts in threat management and vulnerability assessment will also be covered, along with practical demonstrations of how to use SCC Enterprise to identify, investigate, and remediate security risks within your multi-cloud environment.
Google Threat Intelligence provides unmatched visibility into threats by delivering detailed and timely threat intelligence to security teams around the world. This course covers the various capabilities of Google Threat Intelligence and common ways that organizations use this product to proactively mitigate threats.
Hey there! You're invited to game on with the Arcade Trivia for March Week 1! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the March Trivia Week 1 badge!
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
Giriş düzeyindeki BigQuery Verilerinden Analiz Elde Etme beceri rozetini alarak şu konulardaki becerilerinizi gösterin: SQL sorguları yazma, herkese açık tabloları sorgulama, örnek verileri BigQuery'ye yükleme, BigQuery'deki sorgu doğrulayıcı ile yaygın söz dizimi sorunlarını giderme ve BigQuery verilerine bağlanarak Data Studio'da rapor oluşturma.
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
Discover how to turn raw numbers into clear, data-driven decisions on Google Cloud. Through hands-on labs and practical real-world scenarios, this beginner-level course guides you through querying data in BigQuery, exploring trends in Looker, and crafting shareable, interactive reports in Data Studio.
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Network Engineer certification exam. You'll review Gemini Notebook features, add sources to your notebook, and learn how to personalize your Gemini Notebook experience to study for the exam.
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. This course explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. As 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.
As organizations move their data and applications to the cloud, they must address a rapidly evolving landscape of security challenges. This course explores the foundations of cloud security, the value of Google Cloud’s secure-by-design infrastructure, and the defense-in-depth strategy, while highlighting how AI-driven operations and compliance tools help organizations meet strict global regulatory requirements. As 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.
Many traditional enterprises use legacy systems and apps that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems and investing in new products and services. This course explores these challenges and offers solutions to overcome them by using cloud technology. As 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.
Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. Innovating with Google Cloud Artificial Intelligence explores how organizations can use AI and ML to transform their business processes. As 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.
Cloud technology is a powerful asset, and when paired with data, it becomes a catalyst for innovation and enhanced customer experiences. Exploring Data Transformation with Google Cloud examines how organizations can leverage the cloud to make their data more accessible, actionable, and valuable. As 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.
Digital transformation is a critical journey for modern organizations, and establishing a strong baseline in cloud computing is the first step toward driving meaningful innovation. Digital Transformation with Google Cloud introduces the core technologies and strategic frameworks that help organizations modernize their operations. This course explores fundamental cloud concepts, global network infrastructure, and the shared responsibility model to help leaders navigate their path to the cloud with confidence. As 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.
In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
This course provides foundational knowledge for securing your Google Cloud environment. You will learn Google Cloud's security model, including Zero Trust principles and the Shared Fate model. You will configure identity services like Cloud Identity and Workforce Identity Federation, manage access control using Identity and Access Management (IAM) roles, conditions, and policies, and implement network security controls such as VPCs, Cloud Firewall tiers, and VPC Service Controls to build a secure perimeter. As the foundation of the Security in Google Cloud learning path, this course establishes the core principles required for two subsequent specialized tracks: the five-course Security Best Practices in Google Cloud series and the four-course Mitigate Threats in Google Cloud series.
Welcome to the second course in the networking and Google Cloud series routing and addressing. In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities. Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses. By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.
Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals. This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques.
Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Security Engineer certification exam. You'll review Gemini Notebook features, create a notebook, and learn how to use a study guide to practice for the certification exam.
Bu kurs, derin öğrenmeyi kullanarak görüntülere altyazı ekleme modeli oluşturmayı öğretmektedir. Kurs sırasında görüntülere altyazı ekleme modelinin farklı bileşenlerini (ör. kodlayıcı ve kod çözücü) ve modelinizi eğitip değerlendirmeyi öğreneceksiniz. Bu kursu tamamlayan öğrenciler, kendi görüntülere altyazı ekleme modellerini oluşturabilecek ve bu modelleri görüntülere altyazı oluşturmak için kullanabilecek.
Bu kurs, dönüştürücü mimarisini ve dönüştürücülerden çift yönlü kodlayıcı temsilleri (BERT - Encoder Representations from Transformers) modelini tanıtmaktadır. Kursta, öz dikkat mekanizması gibi dönüştürücü mimarisinin ana bileşenlerini ve BERT modelini oluşturmak için dönüştürücünün nasıl kullanıldığını öğreneceksiniz. Ayrıca sınıflandırma, soru yanıtlama ve doğal dil çıkarımı gibi BERT'in kullanılabileceği çeşitli görevler hakkında da bilgi sahibi olacaksınız. Kursun tahmini süresi 45 dakikadır.
Bu kursta, kodlayıcı-kod çözücü mimarisi özet olarak anlatılmaktadır. Bu mimari; makine çevirisi, metin özetleme ve soru yanıtlama gibi "sıradan sıraya" görevlerde yaygın olarak kullanılan, güçlü bir makine öğrenimi mimarisidir. Kursta, kodlayıcı-kod çözücü mimarisinin ana bileşenlerini ve bu modellerin nasıl eğitilip sunulacağını öğreneceksiniz. Laboratuvarın adım adım açıklamalı kılavuz bölümünde ise sıfırdan şiir üretmek için TensorFlow'da kodlayıcı-kod çözücü mimarisinin basit bir uygulamasını yazacaksınız.
Bu kursta nöral ağların, giriş sırasının belirli bölümlerine odaklanmasına olanak tanıyan güçlü bir teknik olan dikkat mekanizması tanıtılmaktadır. Kursta, dikkat mekanizmasının çalışma şeklini ve makine öğrenimi, metin özetleme ve soru yanıtlama gibi çeşitli makine öğrenimi görevlerinin performansını artırmak için nasıl kullanılabileceğini öğreneceksiniz.
Bu kursta, görüntü üretme alanında gelecek vadeden bir makine öğrenimi modelleri ailesi olan "difüzyon modelleri" tanıtılmaktadır. Difüzyon modelleri fizikten, özellikle de termodinamikten ilham alır. Geçtiğimiz birkaç yıl içinde, gerek araştırma gerekse endüstri alanında difüzyon modelleri popülerlik kazandı. Google Cloud'daki son teknoloji görüntü üretme model ve araçlarının çoğu, difüzyon modelleri ile desteklenmektedir. Bu kursta, difüzyon modellerinin ardındaki teori tanıtılmakta ve bu modellerin Vertex AI'da nasıl eğitilip dağıtılacağı açıklanmaktadır.
The Generative AI Explorer - Agent Platform course 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 Gemini models in Agent Platform. 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 custom training in Agent Platform and deploy it to an endpoint in Agent Platform.
Bu kursta Vertex AI Studio tanıtılmaktadır. Bu araç, üretken yapay zeka modelleriyle etkileşime geçmek, kurumsal fikirlerin prototipini oluşturmak ve bunları gerçek hayatta uygulamak için kullanılır. Gerçek hayattan kullanım alanları, etkileşimli dersler ve uygulamalı laboratuvarlar aracılığıyla, ilk istemden son ürüne uzanan yaşam döngüsünü keşfedecek ve çoklu format destekli Gemini uygulamaları, istem tasarımı, istem mühendisliği ve model ayarlama konularında Vertex AI Studio'dan nasıl yararlanabileceğinizi öğreneceksiniz. Bu kursun amacı, Vertex AI Studio'yu kullanarak projelerinizde üretken yapay zekadan yararlanabilmenizi sağlamaktır.
Kurumsal yapay zeka ve makine öğreniminin kullanımı arttıkça, bu teknolojileri sorumlu bir şekilde geliştirmenin önemi de artıyor. Birçok kişi için sorumlu yapay zeka hakkında konuşmak, bunu uygulamaya geçirmekten daha kolaydır. Kuruluşunuzda sorumlu yapay zekayı nasıl hayata geçireceğinizi öğrenmek istiyorsanız bu kurs tam size göre. Bu kursta, kendi sorumlu yapay zeka yaklaşımınızı geliştirirken size rehberlik edecek bir çerçeve oluşturmak adına Google Cloud'un bu süreci günümüzde nasıl yürüttüğünü, en iyi uygulama örneklerini ve edindiğimiz tecrübeleri keşfedeceksiniz.
Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
Giriş seviyesindeki bu mikro öğrenme kursu, sorumlu yapay zekanın ne olduğunu, neden önemli olduğunu ve Google'ın sorumlu yapay zekayı ürünlerinde nasıl uyguladığını açıklamayı amaçlamaktadır. Ayrıca Google'ın 3 yapay zeka ilkesini de tanıtır.
Giriş seviyesindeki bu mikro öğrenme kursunda; büyük dil modellerinin (LLM) ne olduğu, hangi kullanım alanlarında kullanılabilecekleri ve istem ayarlama ile LLM performansını nasıl artırabileceğiniz ele alınmaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da yer almaktadır.
Bu giriş seviyesi mikro öğrenme kursu, üretken yapay zekanın ne olduğunu, nasıl kullanıldığını ve geleneksel makine öğrenimi yöntemlerinden farkını açıklamayı amaçlamaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da ele alınmaktadır.
Google Cloud Computing Foundations kursunda, bulut bilişimi alanında daha önce çalışmamış veya bu konuda hiç deneyimi olmayan bireylere; temel bulut kavramları, büyük veri, makine öğrenimi gibi kavramlar ve Google Cloud'un bu kavramlarla hangi noktada, nasıl birlikte çalıştığı ayrıntılı bir genel bakışla anlatılır. Kursun sonunda öğrenciler bulut bilişimi, büyük veri ve makine öğrenimi konularında fikir yürütüp bazı becerileri pratik olarak sergileyebilecek seviyeye ulaşacaktır. Bu kurs, Google Cloud Computing Foundations adlı kurs serisinin bir parçasıdır. Kurslar aşağıdaki sırayla tamamlanmalıdır: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales İlk kursta bulut bilişimi, Google Cloud'u k…
Google Cloud Computing Foundations kursunda, bulut bilişimi alanında daha önce çalışmamış veya bu konuda hiç deneyimi olmayan bireylere; temel bulut kavramları, büyük veri ve makine öğrenimi gibi kavramlar ve Google Cloud’un bu kavramlarla hangi noktada, nasıl birlikte çalıştığı ayrıntılı bir genel bakışla anlatılır. Kursun sonunda öğrenciler bulut bilişimi, büyük veri ve makine öğrenimi konularında fikir yürütüp bazı becerileri pratik olarak sergileyebilecek seviyeye ulaşacaktır. Bu kurs, Google Cloud Computing Foundations adlı kurs serisinin bir parçasıdır. Kurslar aşağıdaki sırayla tamamlanmalıdır: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales Bu ikinci kursta Google Cloud'da depol…
Güvenli Bir Google Cloud Ağı Oluşturma kursunu tamamlayarak beceri rozeti kazanın. Bu kursta, Google Cloud'da uygulamalarınızı derlemek, ölçeklendirmek ve korumak için ağla ilgili birden fazla kaynak hakkında bilgi edineceksiniz.
Google Cloud Computing Foundations kursunda, bulut bilişimi alanında daha önce çalışmamış veya bu konuda hiç deneyimi olmayan bireylere; temel bulut kavramları, büyük veri ve makine öğrenimi gibi kavramlar ve Google Cloud’un bu kavramlarla hangi noktada, nasıl birlikte çalıştığı ayrıntılı bir genel bakışla anlatılır. Kursun sonunda öğrenciler bulut bilişimi, büyük veri ve makine öğrenimi konularında fikir yürütüp bazı becerileri pratik olarak sergileyebilecek seviyeye ulaşacaktır. Bu kurs, Google Cloud Computing Foundations adlı kurs serisinin bir parçasıdır. Kurslar aşağıdaki sırayla tamamlanmalıdır: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales Bu üçüncü kursta güvenli ağlar oluşturma,…
This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
Welcome to the Learn to Earn Cloud Data Challenge! These labs help you get started with data analysis skills. At the end of each lab, you’ll have hands-on experience with one or more of Google Cloud’s powerful data tools. Complete this game to earn a badge, and you’ll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. 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 quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.
Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating and managing Git repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.
Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.
Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
Complete the intermediate Build a Data Warehouse with BigQuery skill badge course 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.
Welcome to the Learn To Earn Cloud Challenge architecture track! These eight labs give you a blueprint of GCP's building blocks. At the end of each lab, you'll have hands-on experience with another tool or service to add to your resume. Complete this game to earn the Architecture game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
Welcome to the Learn To Earn Cloud Challenge! These eight labs give you a quick hands-on introduction to eight different GCP tools and services. At the end of each lab, you'll have another skill to add to your list. Complete this game to earn the Essentials game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
Welcome to the Learn To Earn Cloud Challenge data track! These eight labs give you a deep dive into GCP's data universe. At the end of each lab, you'll have another in-demand skill to add to your list. Complete this game to earn the Data game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
Welcome to the Learn To Earn Cloud Challenge security track! These eight labs give you the keys to understanding GCP's powerful security suite. At the end of each lab, you'll have hands-on experience with securing your cloud. Complete this game to earn the Security game badge, and you'll be one step closer to collecting all four badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
Google Cloud'da Web Sitesi Derleme beceri rozeti kursunu tamamlayarak giriş düzeyindeki beceri rozetini kazanın. Get Cooking in Cloud serisine dayanan bu kursta şu konular ele alınır:Cloud Run'da web sitesi dağıtmaCompute Engine'de web uygulaması barındırmaGoogle Kubernetes Engine'de web sitenizi oluşturma, dağıtma ve ölçeklendirmeCloud Build'i kullanarak monolitik bir uygulamadan mikro hizmetler mimarisine geçiş
Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.
Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.
Earn a skill badge by completing the Cloud Architecture: Design, Implement, and Manage to demonstrate skills in the following: deploy a publicly accessible website using Apache web servers, configure a Compute Engine VM using startup scripts, configure secure RDP using a Windows Bastion host and firewall rules, build and deploy a Docker image to a Kubernetes cluster and then update it, and create a CloudSQL instance and import a MySQL database. This skill badge is a great resource for understanding topics that will appear in the Google Cloud Certified Professional Cloud Architect certification exam.
Google Cloud Ağınızı Geliştirme kursunu tamamlayarak bir beceri rozeti kazanın. IAM rollerini keşfetme ve proje erişimi ekleme/kaldırma, VPC ağları oluşturma, Compute Engine sanal makinelerini dağıtma ve izleme, SQL sorguları yazma ve çeşitli dağıtım yaklaşımlarıyla Kubernetes'i kullanarak uygulama dağıtma gibi uygulamaları dağıtıp izlemeyle ilgili birden çok yöntemi öğreneceksiniz.
Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma kursunu tamamlayarak beceri rozeti kazanın. Bu kursta Cloud Storage, Identity and Access Management, Cloud Functions ve Pub/Sub gibi teknolojilerin temel özelliklerini kullanarak depolama odaklı bulut altyapısı oluşturma ve bu altyapıyla bağlantı kurmayı öğreneceksiniz.
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.
Giriş düzeyindeki Compute Engine İçin Cloud Load Balancing'i Uygulama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Compute Engine'de sanal makineler oluşturma ve dağıtma. Ağ ve uygulama yük dengeleyicileri yapılandırma.
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.
Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, 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.
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.
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.
This is the second of two courses 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.
Earn a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. 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 quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
Giriş düzeyindeki Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Dataprep by Trifacta ile veri temizleme, Dataflow'da veri ardışık düzenleri çalıştırma, Managed Service for Apache Spark'ta küme oluşturma ve Apache Spark işleri çalıştırma ve makine öğrenimi API'lerini (Cloud Natural Language API, Google Cloud Speech-to-Text API ve Video Intelligence API dahil olmak üzere) çağırma.
Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. 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 quest and the final assessment challenge lab to receive a skill badge that you can share with your network.
Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
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.
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.
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.
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.
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.
It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.