This Generative AI for Software Design and UX Prototyping course equips you with the skills to integrate GenAI tools into modern software development and UI/UX workflows. Begin with foundational concepts to learn the basics of software engineering and how AI enhances architecture design and creative ideation. Progress to applying GenAI in UX design by exploring user behavior prediction, user-centric design principles, and AI-driven design adjustments. Master tools like Uizard to turn text prompts into UI visuals and accelerate prototyping with GenAI. Gain hands-on experience through demos and design exercises that simulate real-world product workflows.

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What you'll learn
Integrate GenAI into software development workflows and architecture design
Use AI tools to generate creative UI/UX concepts and enhance design ideation
Predict user behavior and apply AI for user-centric design improvements
Prototype user interfaces rapidly using tools like Uizard and text-to-visual AI models
Skills you'll gain
Details to know

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July 2025
7 assignments
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There are 2 modules in this course
Explore how Generative AI transforms software design in this foundational module. Learn the basics of software engineering and how AI integrates into development workflows. Understand software architecture design and its enhancement through AI tools. Discover UI/UX design principles and how Generative AI supports creative concept generation.
What's included
6 videos1 reading4 assignments
Learn how Generative AI enhances UX design and prototyping in this hands-on module. Explore user behavior prediction, user-centric design, and AI-driven design adjustments. Discover tools like Uizard and see how AI turns text prompts into detailed UI visuals. Master rapid prototyping techniques using Generative AI to streamline UI/UX workflows.
What's included
8 videos3 assignments
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Frequently asked questions
Generative AI is used to automate code generation, suggest improvements, assist in UI/UX design, and generate test cases—speeding up development and enhancing creativity.
Key principles include adaptability, creativity, user-centric output, ethical alignment, and leveraging large datasets to generate original, context-aware content.
Generative AI typically uses deep learning models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models like GPT.
More questions
Financial aid available,