Sandrina Aulia
Date d'abonnement : 2025
Ligue d'Argent
11625 points
Implement Sensitive Data Protection on Google Cloud
Earned mars 2, 2025 EST
Secure Lakehouse Data
Earned mars 2, 2025 EST
Automate Data Capture at Scale with Document AI
Earned mars 2, 2025 EST
Build Real World AI Applications with Gemini and Imagen
Earned mars 2, 2025 EST
Workspace: Add-ons
Earned mars 1, 2025 EST
Work with Gemini Models in BigQuery
Earned mars 1, 2025 EST
Boost Productivity with Gemini in BigQuery
Earned mars 1, 2025 EST
Responsible AI for Developers: Privacy & Safety
Earned mars 1, 2025 EST
[DEPRECATED] Gemini for Data Scientists and Analysts
Earned mars 1, 2025 EST
Prompt Design in Agent Platform
Earned mars 1, 2025 EST
Complete the Implement Sensitive Data Protection on Google Cloud Skill Badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.
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Complete the introductory Secure Lakehouse Data skill badge course to demonstrate skills with IAM, BigQuery, Lakehouse, and Knowledge Catalog to create and secure Lakehouse tables.
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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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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 Google Cloud Agent Platform. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
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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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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 introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of Google Cloud products and open-source tools.
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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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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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