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Introduction to AI Apps in Sigma

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2 hr
2,150 XP
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Course Description

Build Interactive AI Apps in Sigma

In this course, you’ll learn how to design and build dynamic AI apps in Sigma that actively respond to user input. Rather than relying on static dashboards, you’ll create applications that blend data, logic, and interaction to deliver meaningful, action-oriented experiences. The course focuses on practical app-building techniques that help you guide users, automate workflows, and present insights in intuitive ways.

Capture and Govern User Input

You’ll start with the foundational building blocks of Sigma apps, including linked input tables. These allow you to display warehouse data alongside user-entered values, enabling direct interaction with underlying datasets. You’ll also learn best practices for controlling and governing user input, ensuring accuracy, consistency, and data integrity throughout your app.

Add Interactivity with Modals and Actions

As you progress, you’ll enhance your apps with modals and action sequences. Modals let you surface additional details or collect focused input without cluttering the main interface, while action sequences allow a single user interaction to trigger multiple outcomes. Together, these tools help you create responsive apps that feel intuitive and purposeful.

Refine the User Experience

Finally, you’ll polish your apps using thoughtful layout and design elements such as popovers, buttons, dividers, and tabbed containers. These features help organize content, improve navigation, and create a clean, professional look. By the end of the course, you’ll be equipped to build AI apps in Sigma that are engaging, efficient, and ready for real-world use.

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  1. 1

    How AI Apps automate decision workflows

    Free

    Chapter 1 introduces the foundational concepts behind building AI Apps in Sigma, with a focus on how apps integrate user input to drive action-based workflows. A major emphasis is placed on linked input tables, one of the most important building blocks for Sigma apps. You explore how to create linked input tables that display warehouse data alongside user-entered values, enabling direct interaction with underlying datasets. The chapter also covers best practices for governing user input, including controlling which data types can be entered and defining when tables are editable. By the end of this chapter, you’ll have a strong understanding of how to safely and effectively collect user input while maintaining data integrity within your app.

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    What are AI Apps?
    50 xp
    Exploring a finished app for loan approvals
    100 xp
    A finished app for loan officer promotions
    100 xp
    Enriching existing data with linked input tables
    50 xp
    Understanding linked input tables
    50 xp
    Creating a linked input table
    50 xp
    Capture promotion nominations
    100 xp
    Testing linked input table behaviors
    100 xp
    Governing linked input table data entry
    50 xp
    Managing edits to the loan officers input table
    100 xp
  2. 2

    Adding workflow sequencing to AI Apps

    In Chapter 2, you learn how to make your AI apps more interactive and responsive by using modals and action sequences. Modals allow you to present focused pop-up windows within your app, giving users access to additional information or providing a space for more detailed input without cluttering the main interface. You see how modals can improve usability and guide users through specific tasks. The chapter also introduces action sequences, which enable apps to respond dynamically to user actions such as clicking a button or selecting a table row. You learn how to trigger multiple effects from a single interaction, helping automate workflows and streamline user experiences. Together, modals and action sequences give you powerful tools to build apps that feel intuitive, interactive, and purposeful.

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  3. 3

    Creating cohesive, intuitive AI Apps

    Chapter 3 focuses on refining the user interface and overall experience of your AI apps. You begin by learning about popovers, a versatile UI element used to hide filter menus or display contextual information only when it’s needed. This helps keep apps clean while still providing users with easy access to controls and details. The chapter also explores a range of design and organizational features that enhance both usability and visual appeal. You learn how to incorporate navigational buttons, dividers and tabbed containers to structure content and guide users through your app more effectively. By the end of Chapter 3, you’ll understand how thoughtful layout and design choices can make your AI apps more intuitive, polished, and enjoyable to use.

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collaborators

Collaborator's avatar
Maarten Van den Broeck
Collaborator's avatar
Iason Prassides
Mandy Gray HeadshotMandy Gray

Training and Enablement Lead at Aimpoint Digital

Mandy holds a Masters Degree in Geospatial Information and Technology from the University of Southern California and a Bachelors degree from Harvard College. At Aimpoint Digital, Mandy leads the development and delivery of technical training on a variety of platforms including: Sigma, Dataiku, Alteryx and more. Prior to joining Aimpoint, Mandy spent many years in consulting, M&A and the retail grocery industry.
Klim Kapuka HeadshotKlim Kapuka

Analytics Consultant at Aimpoint Digital

At Aimpoint Digital, Klim focuses on data visualization, workflow automation, and bridging the gap between business strategy and technical insight. He is passionate about helping clients understand their data through visual storytelling and intuitive analytics. Before joining Aimpoint Digital, Klim earned a Master’s degree in Aerospace Engineering from Imperial College London, where he collaborated on projects ranging from wind turbine blade design to space mission planning for Jupiter. He gained hands-on experience as a Data Analyst intern at SC Johnson and as a Machine Learning Engineer at Imperial, where he built sentiment analysis models and deepened his expertise in data modeling and optimization.
Jenny Li HeadshotJenny Li

Analytics Consultant at Aimpoint Digital

Jenny has a strong background in data analytics and business intelligence, with a passion for leveraging data to drive impactful solutions. At Aimpoint Digital she brings expertise in enhancing analytic efficiency and data management. Before joining Aimpoint Digital, Jenny worked as an Analyst Intern at IPSOS. She holds a Master of Science in Business Analytics from Duke University and a Master of Professional Accountancy from the University of California San Diego. Her technical toolkit includes SQL, Python, R, Tableau, and other data analysis and visualization tools.

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