In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
En savoir plus
In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
En savoir plus
In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
En savoir plus
Terminez le badge de compétence avancé Google DeepMind : Entraîner un petit modèle de langage en suivant ce cours pour démontrer les compétences suivantes : formuler des problèmes concrets de recherche sur les modèles de langage, créer un tokenizer simple, préparer un ensemble de données pour entraîner un modèle de langage Transformer, exécuter la boucle d'entraînement d'un petit modèle de langage.Accédez à cet atelier sans frais en souscrivant un abonnement sans frais . Recevez 35 crédits sans frais chaque mois !
En savoir plus
Terminez le cours Implémenter Sensitive Data Protection dans Google Cloud pour recevoir un badge de compétence dans le domaine suivant : utilisation des services Sensitive Data Protection (y compris l'API Cloud Data Loss Prevention) pour inspecter, masquer et supprimer les éléments d'identification des données sensibles dans Google Cloud.
En savoir plus
Obtenez un badge de compétence en suivant le cours Google Cloud Compute : principes de base, où vous apprendrez à utiliser des machines virtuelles (VM), des disques persistants et des serveurs Web à l'aide de Compute Engine.
En savoir plus
Google DeepMind: 03 Design And Train Neural Networks
Earned mars 26, 2026 EDT
Google DeepMind: 02 Represent Your Language Data
Earned jan. 23, 2026 EST
Google DeepMind: 01 Build Your Own Small Language Model
Earned jan. 4, 2026 EST
Google DeepMind : Entraîner un petit modèle de langage
Earned déc. 30, 2025 EST
Implémenter Sensitive Data Protection dans Google Cloud
Earned déc. 24, 2025 EST
Google Cloud Compute : principes de base
Earned oct. 18, 2025 EDT