Overview
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Designed for data professionals, this learning path provides a guide on leveraging BigQuery Machine Learning and Gemini models for advanced data analysis and predictive modeling. You will move beyond theory into practice, learning how to use AI for efficient code generation, troubleshooting, and workflow optimization directly within the Google Cloud console. By the end of this path, you will have applied these concepts in hands-on labs to build, evaluate, and deploy machine learning models that solve real-world business problems.
Syllabus
- Course 1: Gemini for Data Scientists and Analysts
- Course 2: Using BigQuery Machine Learning for inference
- Course 3: Work with Gemini Models in BigQuery
- Course 4: Boost Productivity with Gemini in BigQuery
Courses
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows. Duet AI was renamed to Gemini, our next-generation model.
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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.
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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.
Taught by
Google Cloud Training