With the help of AI, data science teams are now able to automate routine tasks, use previously untapped unstructured data, and achieve new levels of efficiency. This guide helps you get started with data science workflows on Google Cloud and offers a range of real-world use cases (with code) for you to explore.
Streamline your workflows: Learn to build end-to-end data science pipelines on a unified and intelligent data platform, breaking down silos between data and AI
Embrace AI: See how to use generative AI for vector search and multimodal analysis and use agentic AI for automating tedious tasks
Solve real-world use cases: Explore practical, hands-on use cases with code, including modernizing retail demand forecasting, assessing environmental risks, and identifying customer segments
Master modern tools: Get a practical walkthrough of BigQuery, Vertex AI, and other Google Cloud services designed to simplify and scale your data science projects