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Deploy and Manage Generative AI Models

school 7 activités
update Dernière mise à jour : environ 2 mois
person Géré par Google Cloud
This learning path provides a comprehensive introduction to machine learning operations (MLOps), with a specific focus on generative AI. You’ll learn to manage the entire lifecycle of generative AI models, from development and deployment to monitoring. Test your knowledge with a hands-on lab where you'll train and deploy a model in the cloud with Vertex AI.
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Vignette de l'activité pour Machine Learning Operations (MLOps)  for Generative AI
01 Machine Learning Operations (MLOps) for Generative AI
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access_time 30 minutes
show_chart Intermédiaire

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 Vertex AI empowers AI teams to streamline MLOps...

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Vignette de l'activité pour Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
02 Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
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access_time 2 heures 30 minutes
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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...

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Vignette de l'activité pour Responsible AI for Developers: Fairness & Bias
03 Responsible AI for Developers: Fairness & Bias
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access_time 4 heures
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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud...

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Vignette de l'activité pour Responsible AI for Developers: Interpretability & Transparency
04 Responsible AI for Developers: Interpretability & Transparency
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access_time 3 heures
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This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.

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Vignette de l'activité pour Responsible AI for Developers: Privacy & Safety
05 Responsible AI for Developers: Privacy & Safety
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access_time 5 heures
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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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Vignette de l'activité pour Introduction to Security in the World of AI
06 Introduction to Security in the World of AI
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access_time 1 heure
show_chart Débutant

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,...

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Vignette de l'activité pour Build and Deploy Machine Learning Solutions on Vertex AI
07 Build and Deploy Machine Learning Solutions on Vertex AI
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access_time 6 heures 45 minutes
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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions with Vertex AI course, where you will learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain,...

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