BigQuery ML for Inference: Predictive Analytics with SQL

You do not need to be a Python expert or data scientist to leverage the power of machine learning in your data analysis. With BigQuery ML, you can perform advanced predictive analytics and generate model inferences directly where your data lives. This text-based course guides you from SQL basics to deploying and running machine learning models within your data warehouse. You will learn how to make predictions, classify data, and even integrate modern generative AI capabilities using standard SQL queries, streamlining your analytics workflow. In this course, you will: 1. Understand the core concepts of machine learning inference and database-centric workflows. 2. Create and train predictive models directly inside BigQuery using standard SQL syntax. 3. Evaluate model performance using built-in metrics and validation techniques. 4. Generate real-time and batch predictions on large datasets without exporting data. 5. Integrate modern generative AI models and text embeddings for advanced semantic search. 6. Apply best practices for managing, monitoring, and scaling your SQL-based machine learning models. The course begins with foundational definitions of machine learning terms and database structures, ensuring you understand the mechanics of in-database training. From there, you will progress through structured text lessons and written SQL exercises that demonstrate how to implement classification, regression, and modern AI-driven inference. This course is designed for data analysts, SQL developers, and business intelligence professionals who want to add predictive capabilities to their toolkit. No prior machine learning or Python programming experience is required, though a basic familiarity with SQL queries is helpful. Start reading today to unlock the predictive power of your data warehouse.