BigQuery ML: Machine Learning and Inference for Data Analysts

Data analysts often need the power of predictive analytics but struggle with the complexity of exporting massive datasets to external machine learning platforms. BigQuery ML solves this by bringing machine learning capabilities directly to your data warehouse using the SQL skills you already possess. In this comprehensive, text-based course, you will transition from a traditional data analyst to a professional capable of building, evaluating, and deploying machine learning models. You will understand how to generate predictions and run inference directly on your datasets, streamlining your entire analytical workflow. What you'll learn: - Understand the fundamental concepts of machine learning inference and model selection within a data warehouse. - Create and train machine learning models using standard SQL syntax. - Evaluate model performance using built-in evaluation metrics and functions. - Generate batch predictions and run real-time inference on structured data. - Manage and version your models within the cloud environment for clean deployment workflows. - Explore modern features like vector search and embedding generation to handle unstructured data. This written course starts with foundational machine learning definitions and terminology before guiding you through step-by-step SQL code explanations. You will progress from simple linear models to more complex predictive structures, practicing with written exercises and code walkthroughs along the way. This course is designed for data analysts, database administrators, and SQL developers who want to enter the machine learning space. No prior machine learning or programming experience is required, though a basic understanding of SQL queries is recommended. Start reading today to unlock the predictive power of machine learning inside your database.