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Martin Azcarate

Date d'abonnement : 2025

Ligue de bronze

1455 points
Innovating with Google Cloud Artificial Intelligence Earned fév. 6, 2026 EST
Attention Mechanism Earned fév. 4, 2026 EST
Introduction to Image Generation Earned fév. 4, 2026 EST
AI Boost Bites: AI Power-Ups for Google Workspace Earned fév. 4, 2026 EST
Introduction to Responsible AI Earned jan. 30, 2026 EST
Introduction to Large Language Models Earned jan. 30, 2026 EST
Introduction to Generative AI Earned jan. 30, 2026 EST

Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

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This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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