Fine-Tuning Language Models with Azure Databricks

Generic language models are powerful, but to excel with your unique data and specific use cases, fine-tuning is essential. This course guides you step-by-step through the process of adapting pre-trained language models on Azure Databricks, enabling you to build more accurate, context-aware, and performant AI applications. What you'll learn: * Understand the core concepts of language models and the fine-tuning process. * Prepare and manage datasets effectively for custom model training on Databricks. * Configure and execute fine-tuning experiments using Azure Databricks notebooks. * Evaluate the performance of fine-tuned models and iterate on training strategies. * Apply basic prompt engineering techniques to maximize the utility of fine-tuned models. * Explore how fine-tuned models integrate into modern AI architectures like Retrieval Augmented Generation (RAG) systems. Starting with foundational knowledge, the course progresses through data preparation, model training, and performance evaluation, all within the robust Databricks ecosystem. This course is designed for beginners with no prior experience in fine-tuning language models or using Azure Databricks for AI tasks. No prerequisites are required. Start building more intelligent applications today.