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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, and others.
- Benefits and limitations of AI in UI development.
Prompt-Based UI Generation
- Crafting effective prompts for HTML structure and components.
- Generating and adjusting CSS styles with AI assistance.
- Using AI to scaffold interactive elements in JavaScript.
Prototyping Layouts with Generative Tools
- Building landing pages and multi-section layouts.
- Applying responsive design prompts (Flexbox, Grid).
- Previewing and testing designs in CodePen or similar platforms.
Componentization and Reusability
- Creating reusable UI components such as buttons, cards, and forms.
- Developing component libraries and design systems with AI support.
- Applying AI within popular frameworks like React, Vue, and Tailwind.
AI-Assisted Code Review and Debugging
- Resolving layout bugs and accessibility issues using LLMs.
- Optimizing the performance of HTML, CSS, and JS code.
- Understanding errors and obtaining fix suggestions via AI prompts.
Collaborative Design and Content Generation
- Using AI to generate dummy content, copy, and placeholder text.
- Collaborating with designers to co-create wireframes and styles.
- Converting AI-generated concepts into usable HTML templates.
Project: Build an AI-Scaffolded Web App
- Designing the UI based on business requirements.
- Developing components and interactions using AI.
- Polishing, testing, and presenting the prototype.
Summary and Next Steps
Requirements
- Fundamental knowledge of HTML, CSS, and JavaScript.
- Familiarity with front-end frameworks or design systems.
- Interest in using AI to accelerate UI/UX workflows.
Audience
- Front-end developers.
- UX engineers.
- Web designers and creative technologists.
14 Hours
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