成为会员时间：2025
Google DeepMind: 01 Build Your Own Small Language Model
Earned Aug 4, 2026 EDT
使用 Google Cloud 探索数据转换
Earned Jul 31, 2026 EDT
Networking in Google Cloud: Network Architecture
Earned Dec 4, 2025 EST
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.
云技术是一项强大的资产，与数据相结合后，它将成为创新和提升客户体验的催化剂。《使用 Google Cloud 探索数据转换》课程探讨了组织如何利用云技术让数据更易于访问、更具实用价值和商业价值。 作为“Cloud Digital Leader 学习路线”的一部分，本课程旨在帮助个人提升职业素养，并为企业谋求未来发展。
Welcome to the third course of the "Networking in Google Cloud" series: Network Architecture! In this course, you will explore the fundamentals of designing efficient and scalable network architectures within Google Cloud. In the first module, Introduction to Network Architecture, we'll start by introducing you to the core components and concepts of network architecture, including subnets, routes, firewalls, and load balancing. Then in the second module, network topologies, we'll dive into various network topologies commonly used in Google Cloud, discussing their strengths, and weaknesses.