GBQDPGOGoogleGO-GBQDP1.0<ul> <li>Define the features of Gemini in BigQuery that aid the datato-AI pipeline.</li><li>Explore data with Insights and Table Explorer.</li><li>Develop code with Gemini assistance.</li><li>Discover and visualize workflow with data canvas.</li><li>Explain the workflow of using AI/ML models for predictive and generative tasks in BigQuery.</li><li>Create a solution for leveraging Gemini models in BigQuery with SQL queries and Jupyter Notebooks.</li></ul><ul> <li>Prior experience with programming languages including SQL and/or Python.</li><li>Basic knowledge of ML and generative AI.</li></ul><p>Data analysts, data engineers, and other data professionals who wish to use Gemini in BigQuery to boost productivity and understand their unstructured data.</p><h4>Module 1 - Gemini on BigQuery</h4><p> <strong>Topics:</strong></p> <ul> [list] <li>Gemini on Google Cloud</li><li>Overview of Gemini on BigQuery</li><li>Introduction to course use case</li></ul><p> <strong>Objectives:</strong></p> <ul> <li>Understand capabilities of Gemini on Google Cloud.</li><li>Understand capabilities of Gemini on BigQuery.</li></ul><h4>Module 2 - Data Exploration and Preparation</h4><p> <strong>Topics:</strong></p> <ul> <li>Data exploration and preparation</li><li>Insights</li><li>Table Explorer</li></ul><p> <strong>Objectives:</strong></p> <ul> <li>Discover tools that support data exploration.</li><li>Identify the benefits and restrictions of Insights and Table Explorer.</li><li>Explore data cleaning and pipeline development features in BigQuery.</li></ul><p> <strong>Activities:</strong></p> <ul> <li>Lab: Explore Data with Gemini in BigQuery</li></ul><h4>Module 3 - Code Development with Gemini</h4><p> <strong>Topics:</strong></p> <ul> <li>Gemini for writing code</li><li>Troubleshooting and testing with Gemini</li><li>Prompting best practices</li></ul><p> <strong>Objectives:</strong></p> <ul> <li>Explore using Gemini for writing code.</li><li>Identify how Gemini can assist with troubleshooting.</li><li>Discover prompting best practices.</li></ul><p> <strong>Activities:</strong></p> <ul> <li>Lab: Develop Code with Gemini in BigQuery</li></ul><h4>Module 4 - Data Canvas</h4><p> <strong>Topics:</strong></p> <ul> <li>Introduction to Data Canvas</li><li>Data Canvas capabilities</li><li>Prompting best practices for Data Canvas</li></ul><p> <strong>Objectives:</strong></p> <ul> <li>Explore Data Canvas features.</li><li>Discover prompting best practices for Data Canvas.</li></ul><p> <strong>Activities:</strong></p> <ul> <li>Lab: Use Data Canvas to Visualize and Design Queries</li></ul><h4>Module 5 - Working with Gemini Models in BigQuery</h4><p> <strong>Topics:</strong></p> <ul> <li>BigQuery ML</li><li>Using Gemini in your SQL queries</li><li>Gemini in BigQuery Notebooks</li></ul><p> <strong>Objectives:</strong></p> <ul> <li>Discover the capabilities of BigQuery ML.</li><li>Explore using Gemini in your SQL queries.</li><li>Explore using Gemini in Jupyter Notebooks.</li></ul><p> <strong>Activities:</strong></p> <ul> <li>Lab: Analyze Customer Reviews with SQL</li><li>Lab: Analyze Customer Reviews with Python Notebooks</li></ul>- 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.- Prior experience with programming languages including SQL and/or Python. - Basic knowledge of ML and generative AI.Data analysts, data engineers, and other data professionals who wish to use Gemini in BigQuery to boost productivity and understand their unstructured data.Module 1 - Gemini on BigQuery Topics: [list] - Gemini on Google Cloud - Overview of Gemini on BigQuery - Introduction to course use case Objectives: - Understand capabilities of Gemini on Google Cloud. - Understand capabilities of Gemini on BigQuery. Module 2 - Data Exploration and Preparation Topics: - Data exploration and preparation - Insights - Table Explorer Objectives: - Discover tools that support data exploration. - Identify the benefits and restrictions of Insights and Table Explorer. - Explore data cleaning and pipeline development features in BigQuery. Activities: - Lab: Explore Data with Gemini in BigQuery Module 3 - Code Development with Gemini Topics: - Gemini for writing code - Troubleshooting and testing with Gemini - Prompting best practices Objectives: - Explore using Gemini for writing code. - Identify how Gemini can assist with troubleshooting. - Discover prompting best practices. Activities: - Lab: Develop Code with Gemini in BigQuery Module 4 - Data Canvas Topics: - Introduction to Data Canvas - Data Canvas capabilities - Prompting best practices for Data Canvas Objectives: - Explore Data Canvas features. - Discover prompting best practices for Data Canvas. Activities: - Lab: Use Data Canvas to Visualize and Design Queries Module 5 - Working with Gemini Models in BigQuery Topics: - BigQuery ML - Using Gemini in your SQL queries - Gemini in BigQuery Notebooks Objectives: - Discover the capabilities of BigQuery ML. - Explore using Gemini in your SQL queries. - Explore using Gemini in Jupyter Notebooks. Activities: - Lab: Analyze Customer Reviews with SQL - Lab: Analyze Customer Reviews with Python Notebooks1 jour595.00950.00820.00950.00950.00950.00950.00650.00