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heni kothari

Учасник із 2025

Implement Speech and Language Solutions with Pre-trained APIs Earned черв. 10, 2026 EDT
Налаштування середовища для розробки додатка в Google Cloud Earned черв. 5, 2026 EDT
Introduction to Data Analytics on Google Cloud Earned черв. 3, 2026 EDT
Manage Data Models in Looker Earned черв. 3, 2026 EDT
Logic Log Earned черв. 2, 2026 EDT
Skill Up Summer Earned трав. 29, 2026 EDT
Organize and Govern Data with Knowledge Catalog Earned трав. 29, 2026 EDT
Arcade Base Camp May 2026 Earned трав. 27, 2026 EDT
Boost Productivity with Gemini in BigQuery Earned трав. 26, 2026 EDT
Arcade Adventure: Modern App Deployment Earned трав. 25, 2026 EDT
Work with Gemini Models in BigQuery Earned трав. 22, 2026 EDT
Arcade Voyage: Data Governance and Firebase Foundations Earned трав. 22, 2026 EDT
Using BigQuery Machine Learning for Inference Earned трав. 14, 2026 EDT
Using the Google Cloud Speech API Earned трав. 7, 2026 EDT
Work Meets Play: Expressive Efficiency Earned трав. 5, 2026 EDT
Transformer Models and BERT Model Earned трав. 1, 2026 EDT
Running SAP Workloads on Google Cloud: Fundamentals Earned квіт. 30, 2026 EDT
Arcade Adventure: GKE Operations and Networking Earned квіт. 29, 2026 EDT
Works Meet Play: Skills Spawn Earned квіт. 24, 2026 EDT
Agent Assist and its Gen AI Capabilities Earned квіт. 24, 2026 EDT
Implement Cloud Collaboration and Productivity Workflows Earned квіт. 23, 2026 EDT
Gemini for Data Scientists and Analysts Earned квіт. 15, 2026 EDT
Dialogue Design Earned квіт. 15, 2026 EDT
Prompt Design in Agent Platform Earned квіт. 14, 2026 EDT
Explore Generative AI in Agent Platform Earned квіт. 14, 2026 EDT
The Basics of Google Cloud Compute Earned квіт. 10, 2026 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned квіт. 10, 2026 EDT

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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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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In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.

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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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Building a reliable platform for data analysis requires structured data modeling and clean, maintainable code. In this challenge, you’ll start with the building blocks of LookML, creating custom dimensions, measures, and derived tables to shape your data exactly how you need it. From there, you'll work on making your platform faster and easier to use by setting up caching, defining datagroups, and modularizing your code using extends. By following these development best practices, you'll walk away knowing how to build efficient, scalable data models that your team can easily rely on.

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A season to build, experiment, and grow—one skill at a time. You’ll start with the fundamentals of networking, creating the foundation that connects everything together. From there, you’ll step into automation and application development using Cloud Scheduler, App Engine, and machine learning APIs. By the end, you’ll have a more confident, hands-on understanding of how modern applications are built, connected, and run on the cloud.

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Complete the introductory Organize and Govern Data with Knowledge Catalog skill badge to demonstrate skills in the following: creating Knowledge Catalog assets, creating aspect types, and applying aspects to entries in Knowledge Catalog.

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.

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Building and running applications on Google Cloud can take many forms—and this adventure brings them together. Get hands-on with App Engine, Cloud Run, Kubernetes Engine, and Compute Engine as you deploy applications, manage scaling, and explore modern architectures, including the shift from monolithic to microservices.

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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.

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Working with data and applications requires the right balance of governance and agility. In this voyage, you’ll use Dataplex to organize, secure, and assess data quality while exploring concepts like data mesh. Alongside, you’ll get hands-on with Firebase—building serverless apps, working with Firestore, and managing data in real time—bringing together modern data management and application development.

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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.

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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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As platforms grow, maintaining speed, reliability, and seamless user experiences becomes critical. Inspired by Bobble AI and its journey to support millions of real-time interactions, this challenge explores how cloud-native systems are designed for efficiency at scale. You’ll work with Docker and Kubernetes to run and orchestrate applications, while also using IAM, Cloud Storage, and Monitoring to manage access, data, and performance. The result: a clearer view of how the right mix of containers, automation, and observability keeps modern applications fast, resilient, and efficient.

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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.

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Ready to build an AI-ready future for your SAP applications? Modernization isn't just about moving to the cloud anymore—it’s about centralizing your enterprise data so AI agents have the context to make accurate and real-time decisions. In this course, you'll walk away with a clear mental model of the different options to deploy your SAP landscape, centralize your enterprise data, and build impactful agentic solutions.

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Google Kubernetes Engine (GKE) is all about running and managing containerized applications without worrying too much about the underlying setup. In this adventure, you’ll get hands-on with how things actually work—managing workloads, debugging issues, and trying out autoscaling. You’ll also explore Autopilot, run load tests, and work with private clusters and network access. By the end, you’ll have a clearer sense of how GKE setups are put together and handled in practice.

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Online games can get unpredictable. One update drops, a new event goes live—and suddenly, thousands of players are logging in at the same time. That’s where the backend really gets tested. Companies like Com2uS rely on cloud infrastructure to handle exactly this kind of pressure without things falling apart. Here, you’ll work through the same building blocks—setting up networks, handling secure connections, and deploying apps with Docker and Kubernetes. You’ll add authentication, keep an eye on things with logging, and move data when needed. It’s the kind of work that keeps everything running smoothly while players just focus on the game.

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Unlock the power of generative AI to create intelligent, automated agents. After completing this course, you'll be equipped to develop a data store agent that can instantly answer complex questions by automatically extracting and synthesizing information from your websites, documents, or structured data. Say goodbye to static FAQs—your new agent will provide dynamic, accurate answers and even surface the original source URLs, all with a simple and rapid setup. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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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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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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78%—or nearly 8 in 10—business leaders say Google Cloud helps them stay ahead in the age of AI. A big part of that comes down to how teams build and connect intelligent systems. Here, you’ll build and manage conversational agents, and use speech-to-text and translation APIs to handle different types of input. You’ll also move from monolithic apps to microservices on GKE, connect workflows using webhooks, and use observability tools to keep track of what’s happening. IAM comes in as well to manage access where needed. It’s a practical look at how these pieces are used together in real setups.

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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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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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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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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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