Harshit Srivastava
Учасник із 2026
Срібна ліга
Кількість балів: 3782
Gemini for end-to-end SDLC
Earned жовт. 21, 2026 EDT
Using the Google Cloud Speech API
Earned жовт. 20, 2026 EDT
Explore Generative AI in Agent Platform
Earned жовт. 16, 2026 EDT
Store, Process, and Manage Data on Google Cloud - Console
Earned жовт. 15, 2026 EDT
Create Your First Gemini Enterprise Application
Earned жовт. 15, 2026 EDT
Build a Website on Google Cloud
Earned жовт. 15, 2026 EDT
Analyze Images with the Cloud Vision API
Earned жовт. 15, 2026 EDT
Develop AI-Powered Prototypes in Google AI Studio
Earned жовт. 15, 2026 EDT
Implement Speech and Language Solutions with Pre-trained APIs
Earned жовт. 15, 2026 EDT
Configure Service Accounts and IAM Roles for Google Cloud
Earned жовт. 15, 2026 EDT
The Basics of Google Cloud Compute
Earned жовт. 15, 2026 EDT
Streaming Analytics into BigQuery
Earned жовт. 15, 2026 EDT
Use Functions, Formulas, and Charts in Google Sheets
Earned жовт. 14, 2026 EDT
Build LookML Objects in Looker
Earned жовт. 14, 2026 EDT
Implement Cloud Collaboration and Productivity Workflows
Earned жовт. 14, 2026 EDT
Manage Data Models in Looker
Earned жовт. 14, 2026 EDT
Prepare Data for Looker Dashboards and Reports
Earned жовт. 14, 2026 EDT
Analyze BigQuery Data in Connected Sheets
Earned жовт. 14, 2026 EDT
App Building with AppSheet
Earned жовт. 14, 2026 EDT
Prompt Design in Agent Platform
Earned жовт. 14, 2026 EDT
Налаштування середовища для розробки додатка в Google Cloud
Earned жовт. 13, 2026 EDT
Принципи відповідального використання ШІ для розробників: інтерпретованість і прозорість
Earned жовт. 13, 2026 EDT
Принципи відповідального використання ШІ для розробників: об’єктивність і упередженість
Earned жовт. 13, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned жовт. 13, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned жовт. 13, 2026 EDT
Gemini for Data Scientists and Analysts
Earned жовт. 13, 2026 EDT
In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC).
Duet AI was renamed to Gemini, our next-generation model.
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Earn a skill badge by completing the Using the Google Cloud Speech API skill badge course, where you learn how create a Speech-to-Text API request, transcribe audio speech to text, and transcribe speech.
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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. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Create your first Gemini Enterprise application to earn a skill badge! Connect diverse data sources to your application to build a powerful, unified search and analysis engine. Master advanced capabilities like deep research agents, multi-agent ideation, and Gemini Notebook for focused analysis. Explore other content in the Gemini Agent Ready (GEAR) program.
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Earn the introductory skill badge by completing the Build a Website on Google Cloud skill badge course. This course is based on the Get Cooking in Cloud series and covers`:`Deploying a website on Cloud RunHosting a web app on Compute EngineCreating, deploying, and scaling your website on Google Kubernetes EngineMigrating from a monolithic application to a microservices architecture using Cloud Build
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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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Complete the introductory Develop AI-Powered Prototypes in Google AI Studio skill badge to demonstrate skills in the following: crafting effective prompts, leveraging multimodal capabilities for image and video analysis, prototyping functional AI-driven applications from templates and text prompts, and utilizing API keys to build and deploy custom AI solutions. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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.
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Earn the Introductory skill badge by completing the Configure Service Accounts and IAM Roles for Google Cloud course, where you learn about service accounts, custom roles, and how to set permissions using gcloud .
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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 Streaming Analytics into BigQuery skill badge course, where you use Pub/Sub, Dataflow and BigQuery together to stream data for analytics.
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Complete the intermediate Use Functions, Formulas and Charts in Google Sheets skill badge course to demonstrate skills in the following: analyzing data with functions; visualizing data using charts; and searching, validating, formatting, and displaying data.
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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 an introductory skill badge by completing the Implement Cloud Collaboration and Productivity Workflows course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.
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Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.
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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.
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Complete the Analyze BigQuery Data in Connected Sheets skill badge to demonstrate that you can use Connected Sheets to access, analyze, visualize, and share billions of rows of BigQuery data from your Google Sheets spreadsheet.
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Earn a skill badge by completing the App Building with AppSheet course, where you learn how to build, configure, and publish apps using AppSheet.
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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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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У цьому курсі розглядаються поняття інтерпретованості й прозорості штучного інтелекту, а також їх важливість для розробників. Ви дізнаєтеся про практичні методи й інструменти, які дають змогу досягти інтерпретованості й прозорості даних і моделей штучного інтелекту.
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Під час цього курсу ви зможете ознайомитися з концепціями відповідального підходу й принципами щодо штучного інтелекту. Ви дізнаєтеся про практичні методи виявлення об’єктивності й упередженості в роботі ШІ та технологій машинного навчання, а також ознайомитеся зі способами мінімізувати упередженість. У курсі розглядаються практичні методи й інструменти для впровадження відповідального підходу до ШІ за допомогою продуктів Google Cloud і інструментів із відкритим кодом.
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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production.
Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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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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