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Duration 14 hours
Course Outline
Introduction to Generative AI in Front-End Development
- Defining generative AI within the context of software development
- Survey of key tools: ChatGPT, GitHub Copilot, Codeium, and others
- Analyzing the advantages and constraints of AI in UI creation
Generating UIs via Prompt Engineering
- Formulating prompts to define HTML structures and components
- Creating and adjusting CSS styles with AI assistance
- Scaffolding interactive JavaScript elements using AI
Prototyping Layouts with Generative Tools
- Constructing landing pages and complex multi-section layouts
- Crafting responsive design prompts (Flexbox, Grid)
- Previewing and testing outputs in CodePen or equivalent platforms
Componentization and Reusability
- Generating reusable UI elements (buttons, cards, forms)
- Building component libraries and design systems with AI support
- Integrating AI workflows within popular frameworks (React, Vue, Tailwind)
AI-Assisted Code Review and Debugging
- Resolving layout bugs and accessibility issues using LLMs
- Enhancing HTML/CSS/JS performance through optimization
- Interpreting errors and implementing AI-suggested fixes
Collaborative Design and Content Generation
- Utilizing AI to generate placeholder content, copy, and assets
- Collaborating with designers to co-create wireframes and styles
- Converting AI-generated concepts into functional HTML templates
Capstone Project: Building an AI-Scaffolded Web App
- Designing the UI based on a specific business prompt
- Developing components and interactions with AI assistance
- Finalizing, testing, and presenting the prototype
Course Summary and Future Directions
Requirements
- Foundational knowledge of HTML, CSS, and JavaScript
- Experience with front-end frameworks or established design systems
- A strong interest in leveraging AI to streamline UI/UX processes
Intended Audience
- Front-end developers
- UX engineers
- Web designers and creative technologists
Testimonials (1)
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