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Apply your skills in Google Cloud console

Farolina Rahmatunnisa

Учасник із 2024

Бронзова ліга

Кількість балів: 42340
Monitor and Manage Google Cloud Resources Earned серп. 25, 2024 EDT
Create and Manage Cloud SQL for PostgreSQL Instances Earned серп. 25, 2024 EDT
Create and Manage AlloyDB Instances Earned серп. 24, 2024 EDT
Gemini for Data Scientists and Analysts Earned серп. 24, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals - українська Earned серп. 23, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud Earned серп. 23, 2024 EDT
Perform Predictive Data Analysis in BigQuery Earned серп. 23, 2024 EDT
Build LookML Objects in Looker Earned серп. 23, 2024 EDT
Classify Images with TensorFlow on Google Cloud Earned серп. 22, 2024 EDT
Create ML Models with BigQuery ML Earned серп. 21, 2024 EDT
Gemini for Application Developers Earned серп. 20, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned серп. 20, 2024 EDT
Generative AI Explorer - Vertex AI Earned серп. 20, 2024 EDT
Intro to ML: Image Processing Earned серп. 20, 2024 EDT
Intro to ML: Language Processing Earned серп. 20, 2024 EDT
Початок роботи з даними, машинним навчанням і штучним інтелектом Earned серп. 20, 2024 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned лип. 14, 2024 EDT
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI Earned лип. 13, 2024 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud Earned лип. 13, 2024 EDT
Prompt Design in Vertex AI Earned лип. 13, 2024 EDT
Derive Insights from BigQuery Data Earned лип. 13, 2024 EDT
The Basics of Google Cloud Compute Earned лип. 13, 2024 EDT
Get Started with Cloud Storage Earned лип. 13, 2024 EDT
Analyze Speech and Language with Google APIs Earned лип. 13, 2024 EDT
Analyze Sentiment with Natural Language API Earned лип. 13, 2024 EDT
Level 3: GenAIus Travel Guides Earned лип. 12, 2024 EDT
Level 3: GenAIus Travels Earned лип. 12, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud - Yкраїнська Earned лип. 12, 2024 EDT
Introduction to Responsible AI - Українська Earned лип. 12, 2024 EDT
Introduction to Large Language Models - Українська Earned лип. 12, 2024 EDT
Introduction to Generative AI - Українська Earned лип. 12, 2024 EDT
Налаштування середовища для розробки додатка в Google Cloud Earned лип. 12, 2024 EDT
Налаштування Cloud Load Balancing для Compute Engine Earned лип. 11, 2024 EDT
The Arcade June Speedrun Earned лип. 10, 2024 EDT
Level 1: Cloud Connections Earned лип. 9, 2024 EDT
Level 2: Develop and Deploy Earned черв. 29, 2024 EDT
Level 1: Cloud Networking Earned черв. 29, 2024 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned черв. 4, 2024 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 introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.

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Complete the introductory Create and Manage AlloyDB Instances skill badge to demonstrate skills in the following: performing core AlloyDB operations and tasks, migrating to AlloyDB from PostgreSQL, administering an AlloyDB database, and accelerating analytical queries using the AlloyDB Columnar Engine.

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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. Duet AI was renamed to Gemini, our next-generation model.

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Під час курсу ви зможете ознайомитися з продуктами й сервісами Google Cloud для роботи з масивами даних і машинним навчанням, які підтримують життєвий цикл роботи з даними для тренування моделей штучного інтелекту. У курсі розглядаються процеси, проблеми й переваги створення конвеєру масиву даних і моделей машинного навчання з Vertex AI у Google Cloud.

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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.

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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 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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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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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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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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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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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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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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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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Зараз усі говорять про масиви даних, машинне навчання й штучний інтелект, але це досить вузькоспеціалізовані теми, про які важко знайти матеріали, зрозумілі не лише спеціалістам. На щастя, Google Cloud пропонує зручні сервіси в цих галузях, а завдяки цьому вступному курсу ви зможете ознайомитися з такими інструментами, як BigQuery, Cloud Speech API і Video Intelligence.

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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

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Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.

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Пройдіть вступний кваліфікаційний курс Підготовка даних для інтерфейсів API машинного навчання в Google Cloud, щоб продемонструвати свої навички щодо очистки даних за допомогою сервісу Dataprep by Trifacta, запуску конвеєрів даних у Dataflow, створення кластерів і запуску завдань Apache Spark у Dataproc, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API.

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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.

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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.

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Earn a skill badge by completing the Get Started with Cloud Storage skill badge course, where you learn how to create a Cloud Storage bucket, how to use the Cloud Storage command line, and how to use Bucket Lock to protect objects in a bucket.

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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 Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.

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Follow your favorite soccer/football stars as they go for glory in Germany with GenAIus Travel Guides and learn how to interact with chat applications, master prompt engineering, understand AI context, and work with Generative AI—all with no prior experience—and earn an exclusive Google Cloud Generative AI Credential to showcase your skills!

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Excited to follow your favorite soccer/football stars on their next quest? Use GenAIus Travel Guides to learn how to interact with chat applications, master prompt engineering, understand the importance of context in AI, and work with Generative AI. Earn an exclusive Google Cloud Generative AI Credential and showcase your new skills! No prior experience needed!

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Що більше штучний інтелект і машинне навчання використовуються в корпоративних середовищах, то нагальнішою стає потреба розробити принципи відповідального ставлення до них. Однак говорити про принципи відповідального використання штучного інтелекту легше, ніж застосовувати їх на практиці. Цей курс допоможе вам дізнатись, як запровадити відповідальну роботу зі штучним інтелектом у вашій організації. У цьому курсі ви дізнаєтеся про підхід Google Cloud до відповідального використання ШІ, а також отримаєте практичні поради й набудете досвіду, який допоможе вам розробити власний підхід до цього завдання.

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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке відповідальне використання штучного інтелекту, чому воно важливе і як компанія Google реалізує його у своїх продуктах. Крім того, у цьому курсі викладено 7 принципів Google щодо штучного інтелекту.

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У цьому ознайомлювальному курсі мікронавчання ви дізнаєтеся, що таке великі мовні моделі, де вони використовуються і як підвищити їх ефективність коригуванням запитів. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучного інтелекту.

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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке генеративний штучний інтелект, як він використовується й чим відрізняється від традиційних методів машинного навчання. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучногоінтелекту.

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Щоб отримати кваліфікаційний значок, пройдіть курс Налаштування середовища для розробки додатка в Google Cloud. У ньому ви навчитеся створювати й підключати хмарну інфраструктуру, спрямовану на зберігання даних, за допомогою базових можливостей таких технологій, як Cloud Storage, система керування ідентифікацією і доступом, Cloud Functions та Pub/Sub.

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Пройдіть вступний кваліфікаційний курс Налаштування Cloud Load Balancing для Compute Engine, щоб продемонструвати свої навички: створення й розгортання віртуальних машин у Compute Engine; налаштування мережі й розподілювачів навантаження додатків.

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Race to the finish line with the Arcade June Speedrun and pick up valuable skills along with an exclusive Google Cloud Credential. Get hands-on experience with APIs, learn how to build a serverless app, and more! No prior experience needed.

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Constant communications are a thing in the Cloud, with networking connecting all your resources and services. Discover how to manage and optimize these communications using Google Cloud's powerful networking tools, and earn an exclusive Google Cloud Credential—no prior experience needed!

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Bring your ideas to life by gaining hands-on experience in application development and deployment on Google Cloud Platform. Master security, traffic management, and learn to use development frameworks while earning a Google Cloud Credential. No prior experience needed!

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The Cloud hums with constant communication, and the backbone of that connection is networking, linking all your resources and services. Get ready to gain hands-on experience with Google Cloud's powerful networking tools and earn an exclusive Google Cloud Credential—no prior experience needed!

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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 first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.

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