Agiel Asyari
Member since 2019
Silver League
23615 points
Monitor and Manage Google Cloud Resources
Earned Eyl 4, 2024 EDT
Manage Kubernetes in Google Cloud
Earned Eyl 4, 2024 EDT
Build LookML Objects in Looker
Earned Eyl 4, 2024 EDT
Integrate Applications with Gemini on Google Cloud
Earned Eyl 3, 2024 EDT
Gemini for Data Scientists and Analysts
Earned Eyl 3, 2024 EDT
Gemini for Application Developers
Earned Eyl 3, 2024 EDT
Build Infrastructure with Terraform on Google Cloud
Earned Eyl 3, 2024 EDT
Deprecated : Managing Machine Learning Projects with Google Cloud
Earned Eyl 3, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned Eyl 3, 2024 EDT
Intro to ML: Language Processing
Earned Eyl 3, 2024 EDT
Intro to ML: Image Processing
Earned Eyl 3, 2024 EDT
Analyze Speech and Language with Google APIs
Earned Eyl 2, 2024 EDT
Analyze Images with the Cloud Vision API
Earned Eyl 2, 2024 EDT
Analyze Sentiment with Natural Language API
Earned Eyl 2, 2024 EDT
Perform Predictive Data Analysis in BigQuery
Earned Eyl 2, 2024 EDT
Create ML Models with BigQuery ML
Earned Eyl 2, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned Eyl 2, 2024 EDT
Build a Certification Study Guide: PCSE Exam Prep
Earned Eyl 2, 2024 EDT
Generative AI Explorer - Agent Platform
Earned Eyl 2, 2024 EDT
[DEPRECATED] Data Engineering
Earned Nis 2, 2019 EDT
DEPRECATED IoT in the Google Cloud
Earned Mar 30, 2019 EDT
Temel: Veri, Makine Öğrenimi, Yapay Zeka
Earned Mar 21, 2019 EDT
Machine Learning APIs
Earned Mar 20, 2019 EDT
Kubernetes in Google Cloud
Earned Mar 14, 2019 EDT
Google Cloud Essentials
Earned Mar 14, 2019 EDT
Complete the introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.
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Complete the introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.
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This short course on integrating applications with Gemini on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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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.
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Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Find out how you can discover unexpected use cases, recognize the phases of an ML project and considerations within each, and gain confidence to propose a custom ML use case to your team or leadership or translate the requirements to a technical team.
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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.
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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.
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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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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.
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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.
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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.
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Complete the intermediate Perform Predictive Data Analysis in BigQuery skill badge course to demonstrate skills in the following: creating datasets in BigQuery by importing CSV and JSON files; harnessing the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on soccer event data and evaluate the impressiveness of World Cup goals.
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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.
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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.
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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.
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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.
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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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In this quest, you will learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. The labs in this quest use simulator code to mimic IOT devices and the learning here should empower you to implement the same streaming pipeline with real world IoT devices.
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Büyük veri, makine öğrenimi ve yapay zeka bilişim alanında günümüzün popüler konularıdır. Ancak bu alanlar yüksek uzmanlık gerektirir ve giriş seviyesi eğitim materyalleri zor bulunur. Neyse ki Google Cloud, bu alanlarda kullanıcı dostu hizmetler sunuyor ve bu giriş seviyesi kurs sayesinde BigQuery, Cloud Speech API ve Video Intelligence gibi araçlarla ilk adımlarınızı atmanıza imkan tanıyor.
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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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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 course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
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