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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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How AI Apps automate decision workflows
FreeChapter 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.
What are AI Apps?50 xpExploring a finished app for loan approvals100 xpA finished app for loan officer promotions100 xpEnriching existing data with linked input tables50 xpUnderstanding linked input tables50 xpCreating a linked input table50 xpCapture promotion nominations100 xpTesting linked input table behaviors100 xpGoverning linked input table data entry50 xpManaging edits to the loan officers input table100 xp - 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.
Using modals to capture decisions and user input50 xpCreate a modal for capturing promotion nominations100 xpUsing action sequences for app workflows50 xpUnderstanding basic action sequences50 xpCreating an open modal action sequence50 xpTriggering a modal to open and close100 xpPopulating modals with control values50 xpPopulating a modal with loan officer IDs100 xpLog nominations with an action sequence100 xpAdding conditional action sequences50 xpPreventing duplicate nominations100 xp - 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.
Using popovers to simplify an app's interface50 xpConfigure a popover to contain page controls100 xpLeveraging buttons for navigation & interaction50 xpAdding a 'Clear filters' button in a popover100 xpAdding UI & Layout elements for organization50 xpTidying up the loan officer promotions app100 xpBringing it all together100 xpWrap-up50 xp
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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.
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.
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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