🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
GCP200GEMBQ

Gemini in BigQuery for Data Practitioners Training

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.

Google Cloud
✓ Official training Google CloudLevel Intermediate⏱️ 1 day (7h)

What you will learn

  • Define the features of Gemini in BigQuery that aid the data-to-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.

Target audience

  • Data analysts, data engineers, and other data professionals who wish to use Gemini in BigQuery to boost productivity and understand their unstructured data.

Training Program

5 modules to master the fundamentals

Objectives
  • Understand capabilities of Gemini on Google Cloud.
  • Understand capabilities of Gemini on BigQuery.
Topics covered
  • →Gemini on Google Cloud
  • →Overview of Gemini on BigQuery
  • →Introduction to course use case
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.
Topics covered
  • →Data exploration and preparation
  • →Insights
  • →Table Explorer
Activities

Lab: Explore Data with Gemini in BigQuery

Objectives
  • Explore using Gemini for writing code.
  • Identify how Gemini can assist with troubleshooting.
  • Discover prompting best practices.
Topics covered
  • →Gemini for writing code
  • →Troubleshooting and testing with Gemini
  • →Prompting best practices
Activities

Lab: Develop Code with Gemini in BigQuery

Objectives
  • Explore Data Canvas features.
  • Discover prompting best practices for Data Canvas.
Topics covered
  • →Introduction to Data Canvas
  • →Data Canvas capabilities
  • →Prompting best practices for Data Canvas
Activities

Lab: Use Data Canvas to Visualize and Design Queries

Objectives
  • Discover the capabilities of BigQuery ML.
  • Explore using Gemini in your SQL queries.
  • Explore using Gemini in Jupyter Notebooks.
Topics covered
  • →BigQuery ML
  • →Using Gemini in your SQL queries
  • →Gemini in BigQuery Notebooks
Activities

Lab: Analyze Customer Reviews with SQL

Lab: Analyze Customer Reviews with Python Notebooks

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Upcoming sessions

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Quality Process

SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach

Teaching Methods Used
  • Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
  • Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
  • Guided Labs — Guided practical exercises on software, hardware, or technical environments.
  • Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System

The achievement of training objectives is evaluated at multiple levels to ensure quality:

  • Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
  • Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
  • Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.

Frequently Asked Questions

Data analysts, data engineers and data scientists who already work with BigQuery and want to accelerate their data-to-AI workflows with Gemini.
Working knowledge of SQL and basic familiarity with BigQuery are recommended. Some Python experience helps for the notebook exercises.
You will learn how Gemini assists the data-to-AI pipeline in BigQuery: exploring data with Insights and Table Explorer, developing code with AI assistance, using the data canvas, and running generative AI tasks with Gemini models.
Both. The training walks through coding solutions step by step using SQL queries and Python notebooks, around a practical customer-relationship-management use case.
The training lasts 1 day and alternates theory, live demonstrations and hands-on labs in BigQuery.
Our training organizations SFEIR SAS and SFEIR-Est are Qualiopi certified for training activities. Contact us for a quote.

790€ excl. VAT

per learner

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