SQL for Machine Learning with BigQuery

Want to build machine learning models but don't want to learn a new programming language? If you know SQL, you already have the key to building powerful predictive models directly in your data warehouse. This course shows you how to leverage your existing SQL expertise to train, evaluate, and deploy a variety of machine learning models entirely within BigQuery. You will move beyond simple data queries to creating sophisticated forecasting, classification, and clustering models, all using familiar SQL syntax. What you'll learn: - Understand core machine learning concepts and how BigQuery ML simplifies the model development workflow. - Build regression and classification models using SQL to predict numerical values and categorical outcomes. - Apply clustering and dimensionality reduction techniques to uncover hidden patterns and structure in your data. - Create time-series forecasting models to predict future trends and business metrics. - Learn to evaluate model performance, tune hyperparameters, and interpret model predictions for better decision-making. - Practice feature engineering and pre-processing directly within your SQL queries to improve model accuracy. The course starts with the fundamentals of machine learning and the BigQuery ML environment. You'll then progress through text-based exercises for different model types, learning to apply them to practical datasets and business problems. This course is designed for beginners in machine learning. If you are a data analyst, database developer, or BI professional comfortable with SQL, you have everything you need to get started. No prior machine learning or Python programming experience is required. Start building your first machine learning model with SQL today.