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Duration 14 hours
Course Outline
Introductory Concepts: Generative AI in Front-End
- Defining the role of generative AI in software engineering.
- Survey of key tools: ChatGPT, GitHub Copilot, Codeium, and others.
- Evaluating the advantages and constraints of AI in UI construction.
Interface Synthesis via Prompts
- Formulating prompts for HTML architecture and component structure.
- Synthesizing and adjusting CSS styling with AI assistance.
- Scaffolding interactive JavaScript features using AI.
Layout Prototyping with Generative Utilities
- Assembling landing pages and complex multi-section layouts.
- Crafting responsive design prompts utilizing Flexbox and Grid.
- Previewing and validating designs in CodePen or equivalent platforms.
Component Architecture and Reusability
- Generating reusable UI modules such as buttons, cards, and forms.
- Constructing component libraries and design systems with AI support.
- Integrating AI into mainstream frameworks like React, Vue, and Tailwind.
AI-Enhanced Code Analysis and Troubleshooting
- Resolving layout defects and accessibility concerns using LLMs.
- Improving HTML/CSS/JS code efficiency.
- Interpreting errors and generating correction suggestions through AI prompts.
Collaborative Design and Content Synthesis
- Utilizing AI to create placeholder text, copy, and dummy data.
- Partnering with designers to co-develop wireframes and styling.
- Converting AI-generated concepts into functional HTML templates.
Capstone Project: Developing an AI-Assisted Web Application
- Designing the UI architecture based on business requirements.
- Building components and interactions with AI assistance.
- Refining, testing, and showcasing the final prototype.
Recap and Future Directions
Requirements
- Fundamental grasp of HTML, CSS, and JavaScript
- Exposure to front-end frameworks or design systems
- Desire to apply AI techniques to accelerate UI/UX processes
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
