Introduction to Language Models in Azure Databricks

As organizations look to leverage artificial intelligence, integrating large language models with enterprise data has become a critical skill. This text-based course guides you through the foundational concepts of working with language models directly inside the Azure Databricks environment. You will start by understanding key terminology and environment setup before progressing to practical implementation. By the end of this course, you will know how to manage, prompt, and evaluate language models to solve real-world text processing challenges. What you'll learn: - Understand the core architecture of large language models and how they integrate with cloud data platforms. - Configure your Databricks workspace and clusters optimized for machine learning workloads. - Practice basic prompt engineering techniques to guide model outputs effectively. - Explore Retrieval-Augmented Generation (RAG) patterns to connect models to custom data sources. - Track and monitor model parameters and performance using MLflow. This course begins with essential definitions and step-by-step workspace configuration, moving systematically into hands-on code examples and model management workflows. It is designed for beginners, data enthusiasts, and developers who want a practical entry point into modern AI workflows without needing a deep background in machine learning. Start reading today to unlock the power of language models on your data platform.