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Apply your skills in Google Cloud console

Tharun KR

Учасник із 2025

Level 3: Developer Essentials Earned вер. 10, 2025 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned трав. 19, 2025 EDT
Develop Gen AI Apps with Gemini and Streamlit Earned трав. 15, 2025 EDT
Explore Generative AI with the Gemini API in Vertex AI Earned трав. 15, 2025 EDT
Create ML Models with BigQuery ML Earned трав. 13, 2025 EDT
Boost Productivity with Gemini in BigQuery Earned трав. 8, 2025 EDT
Work with Gemini Models in BigQuery Earned трав. 6, 2025 EDT
Prompt Design in Vertex AI Earned трав. 2, 2025 EDT
Build Real World AI Applications with Gemini and Imagen Earned трав. 2, 2025 EDT
Using BigQuery Machine Learning for Inference Earned квіт. 26, 2025 EDT
Gemini for Data Scientists and Analysts Earned квіт. 22, 2025 EDT

From containerization with Docker to scalable databases on Firebase, developer success starts with mastering the essentials. These labs guide you through core skills like container networking and volumes, static site hosting on Cloud Storage, database operations with Firestore in multiple languages, and Linux command-line basics—helping you strengthen the foundation every modern developer needs and earn an exclusive Google Cloud credential!

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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini.

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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.

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Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI 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.

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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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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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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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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 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 Vertex AI platform.

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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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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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