Partecipa Accedi

Keerthana G S

Membro dal giorno 2025

Campionato Argento

4524 punti
Work with Gemini Models in BigQuery Earned mag 12, 2026 EDT
Boost Productivity with Gemini in BigQuery Earned mag 1, 2026 EDT
BigQuery for Data Analysts Earned apr 28, 2026 EDT
Model Armor: Securing AI Deployments Earned apr 14, 2026 EDT
AI responsabile per sviluppatori: privacy e sicurezza Earned apr 14, 2026 EDT
Introduction to Security in the World of AI Earned apr 8, 2026 EDT
AI responsabile per sviluppatori: equità e bias Earned mar 29, 2026 EDT
AI responsabile per sviluppatori: interpretabilità e trasparenza Earned mar 29, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned mar 16, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned feb 22, 2026 EST
[DEPRECATED] Google Cloud: Prompt Engineering Guide Earned feb 17, 2026 EST
Google Cloud Data Analytics Essentials Earned gen 8, 2026 EST
AI Boost Bites: Presentation Scripts with Gemini Earned gen 2, 2026 EST

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 is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision making.

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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 apps. Explore other content in the Gemini Agent Ready (GEAR) program.

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Questo corso introduce argomenti importanti relativi alla privacy e alla sicurezza dell'AI. Esplora metodi e strumenti pratici per implementare le pratiche consigliate per la privacy e la sicurezza dell'AI utilizzando gli strumenti open source e i prodotti Google Cloud.

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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.

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Questo corso introduce i concetti di AI responsabile e i principi dell'AI. Tratta le tecniche per identificare sostanzialmente l'equità e i bias e mitigare i bias nelle pratiche di AI/ML. Illustra metodi e strumenti pratici per implementare le best practice dell'AI responsabile utilizzando gli strumenti open source e i prodotti Google Cloud.

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Questo corso introduce i concetti di interpretabilità e la trasparenza dell'AI. Parla dell'importanza della trasparenza dell'AI per sviluppatori ed engineer. Illustra metodi e strumenti pratici per aiutare a raggiungere interpretabilità e trasparenza sia nei dati che nei modelli di AI.

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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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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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Discover how to turn raw numbers into clear, data-driven decisions on Google Cloud. Through hands-on labs and practical real-world scenarios, this beginner-level course guides you through querying data in BigQuery, exploring trends in Looker, and crafting shareable, interactive reports in Data Studio.

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This video covers how to use Gemini Advanced to research a topic, create a presentation outline, and then use Gemini in Google Docs to generate talking points.

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