Generative AI Fundamentals with Snowflake

Modern organizations are increasingly looking to integrate artificial intelligence directly where their data lives to ensure security, privacy, and efficiency. This text-based course guides you through the transition from traditional data management to building AI-driven solutions using native cloud data capabilities. You will move from understanding the theoretical foundations of artificial intelligence to applying practical techniques for deploying models in a production environment. By focusing on the integration of data and logic, you will learn how to turn raw information into actionable insights using the latest industry tools. What you'll learn: - Understand core generative AI concepts and their integration with cloud data platforms - Apply Cortex LLM functions to perform sentiment analysis, summarization, and translation - Practice prompt engineering techniques to improve model accuracy and relevance - Explore Retrieval-Augmented Generation (RAG) patterns to ground AI responses in private data - Learn the process of fine-tuning foundation models for specialized business tasks - Understand data governance and privacy best practices when deploying AI models The course begins with essential terminology and environment configuration before moving into the implementation of built-in AI functions and advanced model customization. You will progress through written explanations and code-based exercises designed to reinforce technical concepts. This course is designed for beginners and data professionals who want to expand their technical toolkit. No prior experience with artificial intelligence or machine learning is required to begin. Start building modern AI applications on your data platform today.