Data Analytics and Machine Learning Pipelines on GCP

In today's data-driven world, traditional analytics are no longer enough to stay competitive. By integrating machine learning directly into your cloud data pipelines, you can uncover predictive insights that drive real business value. This text-based course guides you through the core concepts of smart analytics and AI on GCP. You will transition from understanding basic cloud data storage to designing automated pipelines that leverage built-in machine learning models for advanced predictions. What you'll learn: Understand foundational cloud data concepts, including data lakes, data warehouses, and modern ELT processes; Build scalable data pipelines on GCP using core analytics tools like BigQuery; Apply machine learning models directly within your SQL queries using BigQuery ML; Explore modern AI capabilities on GCP, including Vertex AI and basic generative AI integration; Design automated workflows to clean, transform, and analyze large datasets; Practice evaluating model performance and deploying predictive insights to business dashboards. You will start with essential terminology and cloud architecture basics before moving step-by-step through pipeline design and model integration. The written format allows you to study detailed SQL and architectural examples at your own pace. This course is designed for beginner data analysts, cloud novices, and aspiring data engineers who want to learn cloud-based AI. No prior experience with GCP or machine learning is required. Start building smarter, AI-driven data pipelines on the cloud today.