Course Overview of Gemini in BigQuery for Data Practitioners

This instructor-led course demonstrates how to use Gemini in BigQuery for Generative AI and AI/ML-powered analytics workflows. Through practical business scenarios involving customer relationship management and unstructured data analysis, learners will explore how Gemini enhances productivity across the data-to-AI lifecycle. 

Participants will learn how to explore and prepare data using Insights and Table Explorer, develop code with Gemini assistance, visualize workflows using Data Canvas, and leverage BigQuery ML and Gemini models for predictive and generative AI tasks. The course also provides guided implementation using SQL queries and Python notebooks for practical AI-powered analytics solutions. 

Through hands-on labs and real-world use cases, learners will gain practical experience integrating Gemini capabilities into modern data analytics and machine learning workflows on Google Cloud.  

After completing Gemini in BigQuery for Data Practitioners, students will be able to:

  • Define the capabilities of Gemini in BigQuery.
  • Explore and prepare data using Insights and Table Explorer.
  • Use Gemini assistance for code generation and troubleshooting.
  • Visualize workflows and queries using Data Canvas.
  • Apply prompting best practices for Gemini workflows.
  • Understand predictive and generative AI workflows in BigQuery.
  • Build AI-powered analytics solutions using BigQuery ML.
  • Integrate Gemini models into SQL queries and Jupyter Notebooks.
  • Analyze structured and unstructured data using Gemini.
  • Develop data-to-AI workflows using BigQuery and Vertex AI

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Key Features of Gemini in BigQuery for Data Practitioners

  • AI-Powered Data Analytics Training

  • Hands-On Learning Experience

  • Data Exploration and Preparation 

  •  AI-Assisted Code Development

  • Data Canvas and Workflow Visualization

  • BigQuery ML and Gemini Integration 

  • Google Cloud AI and Analytics Ecosystem Exposure 

  •  Enterprise Data-to-AI Workflow Best Practices 

Who should Attend Gemini in BigQuery for Data Practitioners?

  • Data Analysts
  • Data Engineers
  • Analytics Engineers
  • AI Practitioners
  • Cloud Data Professionals
  • BI Professionals
  • Developers working with BigQuery and Generative AI
  • Professionals interested in AI-powered analytics workflows

Prerequisites of Gemini in BigQuery for Data Practitioners

  • Prior experience with SQL and/or Python programming
  • Basic knowledge of machine learning concepts
  • Basic understanding of Generative AI
  • Familiarity with data analytics workflows is recommended
  • Interest in AI-powered analytics and data exploration

    • Why choose CloudThat as your training partner for Gemini in BigQuery for Data Practitioners?

    •  Specialized Google Cloud AI and Analytics Expertise - CloudThat specializes in cloud, analytics, and Generative AI technologies, delivering industry-focused Google Cloud AI training programs with practical enterprise implementation experience. 
    • Industry-Recognized Trainers - Our trainers are certified Google Cloud professionals with expertise in BigQuery, Gemini, Vertex AI, analytics engineering, and AI-powered data workflows. 
    • Hands-On Learning Approach -CloudThat emphasizes practical learning through guided labs, SQL-based exercises, notebook workflows, AI-assisted analytics scenarios, and real-world business use cases.
    • Customized Learning Paths - Training programs are designed for data analysts, data engineers, AI practitioners, and cloud professionals with varying levels of analytics and AI expertise. 
    • Interactive and Practical Sessions - Sessions include demonstrations, architecture discussions, troubleshooting exercises, analytics workflows, and collaborative AI activities. 
    • Career and Certification Support- CloudThat supports learners with analytics project guidance, interview preparation, and practical enterprise AI implementation strategies.
    • Updated Industry-Relevant Content- Course content is continuously updated to align with the latest advancements in Gemini, BigQuery, AI-assisted analytics, and Generative AI technologies.
    • Trusted by Enterprises Worldwide- Thousands of professionals and organizations trust CloudThat for advanced cloud, analytics, AI, and Generative AI training programs. 

    Learning Objective of Gemini in BigQuery for Data Practitioners

    • Understand Gemini capabilities within BigQuery.
    • Explore and prepare data using AI-assisted workflows.
    • Utilize Gemini for code generation and troubleshooting.
    • Build visual analytics workflows using Data Canvas.
    • Apply prompt engineering best practices for analytics use cases. 
    •  Implement predictive and generative AI workflows using BigQuery ML. 
    • Integrate Gemini models into SQL queries and notebooks.
    • Analyze structured and unstructured business data.
    • Build enterprise-ready AI-powered analytics solutions. 
    • Improve productivity across the data-to-AI lifecycle.

    Course Outline for Gemini in BigQuery for Data Practitioners Download Course Outline

    Lecture Content

    • Gemini on Google Cloud
    • Overview of Gemini on BigQuery
    • Introduction to Course Use Case
    • Data-to-AI Workflow Concepts
    • AI Productivity Features in BigQuery

    Learning Objectives

    • Understand the capabilities of Gemini on Google Cloud
    • Explore Gemini capabilities within BigQuery
    • Identify AI-powered analytics workflows for business use cases

    Lecture Content

    • Data Exploration and Preparation
    • Insights
    • Table Explorer
    • Data Cleaning and Pipeline Development Features
    • Analytics Workflow Preparation Techniques

    Learning Objectives

    • Discover tools that support data exploration
    • Identify benefits and limitations of Insights and Table Explorer
    • Explore data cleaning and preparation workflows in BigQuery
    • Understand modern analytics preparation techniques

    Lab Content

    • Explore Data with Gemini in BigQuery

    Lecture Content

    • Gemini for Writing Code
    • Troubleshooting and Testing with Gemini
    • Prompting Best Practices
    • AI-Assisted SQL and Python Development
    • Developer Productivity Enhancement Workflows

    Learning Objectives

    • Use Gemini for generating SQL and Python code
    • Troubleshoot and optimize code using Gemini assistance
    • Apply prompting best practices for AI-assisted development
    • Accelerate analytics workflows using Generative AI

    Lab Content

    • Develop Code with Gemini in BigQuery

    Lecture Content

    • Introduction to Data Canvas
    • Data Canvas Capabilities
    • Prompting Best Practices for Data Canvas
    • Query Visualization Workflows
    • Visual Analytics Design Concepts

    Learning Objectives

    • Explore Data Canvas features and workflows
    • Design visual analytics workflows using Data Canvas
    • Apply prompting strategies for visual query generation
    • Build visualized analytics workflows in BigQuery

    Lab Content

    • Use Data Canvas to Visualize and Design Queries

    Lecture Content

    • BigQuery ML
    • Using Gemini in SQL Queries
    • Gemini in BigQuery Notebooks
    • AI-Powered Data Analysis Workflows
    • Generative AI and Predictive Analytics Concepts

    Learning Objectives

    • Understand BigQuery ML capabilities and workflows
    • Integrate Gemini models into SQL queries
    • Use Gemini within Jupyter Notebooks
    • Build predictive and generative AI analytics solutions

    Lab Content

    • Analyze Customer Reviews with SQL
    • Analyze Customer Reviews with Python Notebooks

    Certification Details of Gemini in BigQuery for Data Practitioners

      CloudThat Course Completion Certificate

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    Course ID: 28576

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    FAQs for Gemini in BigQuery for Data Practitioners

    This course is designed for data analysts, data engineers, and professionals interested in using Gemini in BigQuery for AI-powered analytics workflows.

    The course covers Gemini in BigQuery, data exploration, AI-assisted code development, Data Canvas, BigQuery ML, and Generative AI workflows.

    Yes, prior experience with SQL and/or Python is recommended.

    The course duration is approximately 1 day instructor-led training.

    Yes, the course includes practical labs focused on data exploration, code development, Data Canvas, SQL analysis, and notebook-based workflows.

    Gemini in BigQuery provides AI-powered assistance for analytics workflows including data exploration, code generation, visualization, and predictive AI tasks.

    Yes, learners will explore BigQuery ML capabilities and AI-powered analytics workflows.

    Yes, the course includes Generative AI workflows using Gemini models within BigQuery and notebooks.

    The course includes Gemini, BigQuery, Vertex AI, BigQuery ML, Data Canvas, and Jupyter Notebooks.

    Yes, this is an intermediate-level course intended for professionals familiar with SQL, Python, and basic AI/ML concepts.

    Enquire Now