Introducing “How Transformer LLMs Work,” created with Jay Alammar and Maarten Grootendorst, authors of the “Hands-On Large Language Models” book...

In Retrieval Optimization: From Tokenization to Vector Quantization, taught by Kacper Łukawski, Developer Relations Lead of Qdrant, you’ll learn all about tokenization and also how to optimize vect...

Prompt engineering is used not only in text models but also in vision models...

Retrieval Augmented Generation (RAG) stands out as one of the most popular use cases of large language models (LLMs)...

The Vertex AI Text-Embeddings API enhances the process of generating text embeddings...

This course focuses on integrating traditional database features with vector search capabilities to optimize the performance and cost-efficiency of large-scale Retrieval Augmented Generation (RAG) ...

Join our new short course, Improving Accuracy of LLM Applications with Lamini and Meta...

Learn how to build AI agents that interact with websites in Building AI Browser Agents, taught by Div Garg and Naman Garg, Co-founders of AGI Inc, and built in partnership with AGI Inc.

Instructors: Russ d’Sa, Shayne Parmelee, Nedelina Teneva