Vertex AI Forecasting and Time Series Analysis

Accurate forecasting is critical for businesses predicting demand, sales, or resource needs, but building scalable time series models can be complex. This written course guides you through leveraging Vertex AI to design and deploy production-ready forecasting solutions. You will transition from understanding basic time series concepts to structuring data, training advanced forecasting models, and deploying them to generate actionable predictions. What you'll learn: Understand core time series concepts, including trend, seasonality, and sequence models; Prepare and structure historical data specifically for machine learning forecasting workflows; Configure and train forecasting models using AutoML and custom training pipelines in Vertex AI; Evaluate model performance using key metrics like MAE, RMSE, and MAPE; Deploy trained forecasting models to endpoints for batch and real-time predictions; Apply modern MLOps practices to monitor model drift and automate pipeline runs. You will begin with foundational definitions and data preparation requirements, then progress through model configuration, evaluation, and deployment. This course is designed for beginners, data analysts, and developers looking to expand their machine learning toolkit, with no advanced prerequisites required. Start reading today to master cloud-based time series forecasting.