Chanatda Konchom
Учасник із 2026
Срібна ліга
Кількість балів: 1916
Implement Multimodal Vector Search with BigQuery
Earned квіт. 9, 2026 EDT
Perform Predictive Data Analysis in BigQuery
Earned квіт. 8, 2026 EDT
Use APIs to Work with Cloud Storage
Earned квіт. 8, 2026 EDT
Enhance Gemini Model Capabilities
Earned квіт. 7, 2026 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned квіт. 6, 2026 EDT
Prompt Design in Agent Platform
Earned квіт. 4, 2026 EDT
Manage Kubernetes in Google Cloud
Earned квіт. 2, 2026 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned бер. 30, 2026 EDT
Create ML Models with BigQuery ML
Earned бер. 28, 2026 EDT
Configure Service Accounts and IAM Roles for Google Cloud
Earned бер. 26, 2026 EDT
Model Armor: Securing AI Deployments
Earned бер. 25, 2026 EDT
Vector Search and Embeddings
Earned бер. 24, 2026 EDT
Build Serverless Applications with Cloud Run Functions
Earned бер. 23, 2026 EDT
Automate Data Capture at Scale with Document AI
Earned бер. 21, 2026 EDT
Gemini for Security Engineers
Earned бер. 19, 2026 EDT
Complete the intermediate Implement Multimodal Vector Search with BigQuery skill badge to demonstrate skills in the following: using Gemini in BigQuery to generate and debug SQL, conduct sentiment analysis, summarize text and identify keywords, generate embeddings, create a Retrieval Augmented Generation (RAG) pipeline, and implement multimodal vector search.
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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 Use APIs to Work with Cloud Storage skill badge to demonstrate skills in the following: using APIs to work with Cloud Storage resources, including the Cloud Storage API.
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Complete the intermediate Enhance Gemini Model Capabilities skill badge to demonstrate skills in the following: leveraging advanced features of Gemini models, including code generation and execution, grounding, controlled content generation, and synthetic data creation, to build more powerful and sophisticated AI applications.
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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. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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 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 intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.
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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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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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This course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Earn a Introductory skill badge by completing the Build Serverless Applications with Cloud Run Functions course, where you learn how to use Cloud Run functions through the Google Cloud console and on the command line.
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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture.
Duet AI was renamed to Gemini, our next-generation model.
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