Jamaludin Ahmad Rifai C459D4KY0090
Member since 2024
Diamond League
49625 points
Member since 2024
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.
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
Complete the intermediate Explore Generative AI in Agent Platform skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.
Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run.
Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.
Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you 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.
Orta düzeydeki Çoklu Format Destekli Gemini ve Çok Formatlı RAG ile Zengin Belgeleri İnceleme beceri rozetini tamamlayarak şu konulardaki becerilerinizi kanıtlayabilirsiniz: Çok formatlı istemler kullanarak metin ve görsel formatlarındaki verilerden bilgi elde etme, video açıklaması oluşturabilme ve Gemini ile çok formatlılıktan yararlanarak videonun kapsamındaki bilgilerden çok daha fazlasına ulaşabilme; metin ve görüntü içeren dokümanların meta verilerini oluşturma, gerekli tüm metin parçalarına ulaşma ve Gemini'ın Çok Formatlı Almayla Artırılmış Üretim (RAG) mimarisini kullanarak alıntıları yazdırma.
Complete the intermediate Secure Software Delivery skill badge to demonstrate your proficiency in proactively integrating security into the software development lifecycle (SDLC) with DevSecOps principles. You'll learn how to utilize Google Kubernetes Engine (GKE) and Cloud Run for secure container image deployment, implement automated vulnerability scanning to proactively identify risks, and streamline application development with Artifact Registry while maintaining a focus on security. Additionally, you'll gain skills in integrating Cloud Build for robust development processes and implementing Admission Control Policies for fine-grained control over your environment.
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.
Complete the introductory Secure Lakehouse Data skill badge course to demonstrate skills with IAM, BigQuery, Lakehouse, and Knowledge Catalog to create and secure Lakehouse tables.
Complete the introductory Get Started with Sensitive Data Protection skill badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.
Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
Earn the Introductory Skill Badge by completing the Implement Speech and Language Solutions with Pre-trained APIs course, where you learn how to use speech related API tools to synthesise and transcribe speech.
Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Google Cloud Agent Platform.
Agent Platform'da istem mühendisliği, görüntü analizi ve çok modlu üretken teknikler gibi becerileri göstermek için Agent Platform'da İstem Tasarımı beceri rozetini tamamlayın. Etkili istemlerin nasıl oluşturulacağını, üretken yapay zeka çıktılarına nasıl rehberlik edileceğini ve Gemini modellerinin gerçek dünyadaki pazarlama senaryolarına nasıl uygulanacağını keşfedin.
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.
This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to on Google Cloud using Cloud Run.design, implement, deploy, secure, manage, and scale applications
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.
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.
This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.
Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud. The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.
Learn how to use NotebookLM to create a personalized study guide for the Associate Cloud Engineer certification exam. You'll review NotebookLM features, create a notebook in NotebookLM, and learn how to use a study guide to practice for a certification exam.
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.
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.
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.
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.
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.
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.
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,…
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…
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…