This learning path provides a journey into leveraging Gemini within BigQuery for advanced data and AI workflows. Starting with foundational productivity enhancements, it progresses to building generative AI applications and culminates in mastering Retrieval Augmented Generation to mitigate AI inaccuracies. By completing this path, learners will gain practical skills in utilizing Gemini to streamline data processes, create innovative AI solutions, and ensure reliable AI outputs within the BigQuery environment.

Praktisches Lernprojekt

This learning path provides a comprehensive guide to using Gemini in BigQuery to accelerate your AI/ML projects. You'll gain practical experience defining Gemini's features, exploring data with insights, and developing code efficiently with Gemini assistance. You'll also explore the end-to-end process of using AI/ML models for predictive and generative tasks, and build a complete solution leveraging Gemini models in BigQuery. Master the techniques of generating embeddings, performing vector searches, and building Retrieval Augmented Generation (RAG) pipelines. This path will equip you with the skills to effectively integrate Gemini into your BigQuery workflows, enabling you to create powerful, data-driven applications.