Menjadi anggota sejak 2025
Google DeepMind: 02 Represent Your Language Data
Earned Des 30, 2025 EST
Pengantar Model Bahasa Besar
Earned Des 19, 2025 EST
Berinovasi dengan Kecerdasan Buatan Google Cloud
Earned Des 19, 2025 EST
Google DeepMind: 01 Build Your Own Small Language Model
Earned Des 18, 2025 EST
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.
Ini adalah kursus pengantar pembelajaran mikro yang membahas definisi model bahasa besar (LLM), kasus penggunaannya, dan cara menggunakan prompt tuning untuk meningkatkan performa LLM. Kursus ini juga membahas beberapa alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.
Kecerdasan buatan (AI) dan machine learning (ML) mewakili evolusi penting dalam teknologi informasi yang dengan cepat mentransformasi berbagai industri. Berinovasi dengan Kecerdasan Buatan Google Cloud membahas cara organisasi menggunakan AI dan ML untuk mentransformasi proses bisnis mereka. Sebagai bagian dari alur pembelajaran Cloud Digital Leader, kursus ini bertujuan membantu individu berkembang dalam peran mereka dan membangun masa depan bisnis mereka.
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.