成为会员时间：2025
Google DeepMind: 03 Design And Train Neural Networks
Earned Mar 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：训练小语言模型
Earned Dec 30, 2025 EST
在 Google Cloud 中实施 Sensitive Data Protection
Earned Dec 24, 2025 EST
Google Cloud 云计算基础知识
Earned Oct 18, 2025 EDT
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.
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.
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.
完成本课程，赢取 Google DeepMind：训练小语言模型高级技能徽章，展示您在以下方面的技能： 提出实际的语言模型研究问题；构建一个简单的词元化器；制作用于训练 Transformer 语言模型的数据集；运行小语言模型的训练循环。 注册免费订阅，即可免费访问此实验。每月可免费获得 35 个点数！
完成 在 Google Cloud 中实施 Sensitive Data Protection 这一入门级技能徽章课程，展示您在以下方面的技能：使用 Sensitive Data Protection 服务 （包括 Cloud Data Loss Prevention API）来检查和隐去 Google Cloud 中的敏感数据，并对敏感数据进行去标识处理。
完成Google Cloud 云计算基础知识挑战任务，赢取技能徽章。 您将学习如何在 Compute Engine 中使用虚拟机 (VM)、永久性 磁盘和 Web 服务器。