Gemini in BigQuery for Data Practitioners
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.
- Duration: 1 day
- Languages: English, German
- Level: Intermediate
- Group size: Up to 16
What you'll learn
- Define the features of Gemini in BigQuery that aid the datato-AI pipeline.
- Explore data with Insights and Table Explorer.
- Develop code with Gemini assistance.
- Discover and visualize workflow with data canvas.
- Explain the workflow of using AI/ML models for predictive and generative tasks in BigQuery.
- Create a solution for leveraging Gemini models in BigQuery with SQL queries and Jupyter Notebooks.
Prerequisites
- Prior experience with programming languages including SQL and/or Python.
- Basic knowledge of ML and generative AI.
Course outline
Gemini on BigQuery
- Gemini on Google Cloud
- Overview of Gemini on BigQuery
- ntroduction to course use case
Data Exploration and Preparation
- Data exploration and preparation
- Insights
- Table Explorer
Code Development with Gemini
- Gemini for writing code
- Troubleshooting and testing with Gemini
- Prompting best practices
Data Canvas
- Introduction to Data Canvas
- Data Canvas capabilities
- Prompting best practices for Data Canvas
Working with Gemini Models in BigQuery
- BigQuery ML
- Using Gemini in your SQL queries
- Gemini in BigQuery Notebooks
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Not sure which course fits?
Book a 30-minute call. We'll look at where your team is, what they need to be able to do, and put together either a specific course date or a tailored learning plan.