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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.
- An overview of key tools such as ChatGPT, GitHub Copilot, and Codeium.
- Exploring the benefits and limitations of AI in UI development.
Prompt-Based UI Generation
- Crafting effective prompts to generate HTML structures and components.
- Generating and adjusting CSS styles using AI capabilities.
- Leveraging AI to scaffold interactive elements in JavaScript.
Prototyping Layouts with Generative Tools
- Constructing landing pages and multi-section layouts.
- Employing responsive design prompts for Flexbox and Grid systems.
- Previewing and testing implementations in CodePen or comparable platforms.
Componentization and Reusability
- Creating reusable UI components, including buttons, cards, and forms.
- Developing component libraries and design systems with AI assistance.
- Integrating AI within popular frameworks like React, Vue, and Tailwind.
AI-Assisted Code Review and Debugging
- Resolving layout bugs and accessibility issues using LLMs.
- Enhancing the performance of HTML/CSS/JS code.
- Interpreting errors and suggesting solutions through AI prompts.
Collaborative Design and Content Generation
- Utilizing AI to generate dummy content, copy, and placeholders.
- Collaborating with designers to co-create wireframes and styles.
- Converting AI-generated concepts into functional HTML templates.
Project: Building an AI-Scaffolded Web App
- Designing the UI based on specific business prompts.
- Developing components and interactions with AI support.
- Refining, testing, and presenting the final prototype.
Summary and Next Steps
Requirements
- Foundational knowledge of HTML, CSS, and JavaScript.
- Familiarity with front-end frameworks or established design systems.
- A keen interest in applying AI to streamline UI/UX workflows.
Target 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
