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Course Outline
Introduction to Generative AI for Front-End
- Understanding generative AI in software development.
- Overview of tools: ChatGPT, GitHub Copilot, Codeium, etc.
- Benefits and limitations of AI in UI development.
Prompt-Based UI Generation
- Crafting prompts for HTML structure and components.
- Generating and modifying CSS styles with AI.
- Using AI to scaffold interactive elements in JavaScript.
Prototyping Layouts with Generative Tools
- Building landing pages and multi-section layouts.
- Responsive design prompts (Flexbox, Grid).
- Previewing and testing in CodePen or similar tools.
Componentization and Reusability
- Generating reusable UI components (buttons, cards, forms).
- Creating component libraries and design systems with AI assistance.
- Integrating AI into popular frameworks (React, Vue, Tailwind).
AI-Assisted Code Review and Debugging
- Resolving layout bugs and accessibility issues with LLMs.
- Optimizing HTML/CSS/JS code performance.
- Explaining errors and suggesting fixes via AI prompts.
Collaborative Design and Content Generation
- Using AI to generate dummy content, copy, and placeholders.
- Collaborating with designers to co-create wireframes and styles.
- Translating AI-generated ideas into usable HTML templates.
Project: Build an AI-Scaffolded Web App
- Designing UI based on business prompts.
- Building components and interactions using AI.
- Polishing, testing, and presenting the prototype.
Summary and Next Steps
Requirements
- Foundational knowledge of HTML, CSS, and JavaScript
- Familiarity with front-end frameworks or design systems
- Interest in utilizing AI to accelerate UI/UX workflows
Target Audience
- Front-end developers
- UX engineers
- Web designers and creative technologists
14 Hours
Testimonials (2)
The session was highly interactive and applicable to the business.
Jorge Boscan - Chevron Global Technology Services Company
Course - Advanced GitHub Copilot & AI for Projects and Infrastructure
Machine Translated
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny