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Duration 14 hours
Course Outline
Introduction to Generative AI in Front-End Development
- Understanding the role of generative AI in software engineering.
- An overview of key tools including ChatGPT, GitHub Copilot, and Codeium.
- Examining the advantages and constraints of AI in UI development.
Generating UIs via Prompt Engineering
- Formulating effective prompts to generate HTML structures and components.
- Creating and adjusting CSS styles with the aid of AI.
- Leveraging AI to scaffold interactive JavaScript elements.
Rapid Layout Prototyping with Generative Tools
- Constructing landing pages and complex multi-section layouts.
- Crafting responsive design prompts utilizing Flexbox and Grid.
- Previewing and testing implementations using platforms like CodePen.
Focus on Componentization and Reusability
- Generating reusable UI components such as buttons, cards, and forms.
- Building component libraries and design systems with AI assistance.
- Integrating AI workflows within popular frameworks like React, Vue, and Tailwind.
AI-Enhanced Code Review and Debugging
- Resolving layout bugs and accessibility issues using Large Language Models (LLMs).
- Optimizing the performance of HTML, CSS, and JavaScript code.
- Interpreting error messages and deriving solutions through AI prompts.
Collaborative Design and Content Creation
- Utilizing AI to generate placeholder text, copy, and dummy content.
- Collaborating with designers to co-create wireframes and visual styles.
- Converting AI-generated concepts into functional HTML templates.
Capstone Project: Developing an AI-Scaffolded Web Application
- Designing the user interface based on specific business prompts.
- Constructing components and interactions with AI support.
- Finalizing, testing, and presenting the completed prototype.
Conclusion and Future Pathways
Requirements
- Foundational knowledge of HTML, CSS, and JavaScript.
- Basic familiarity with front-end frameworks or established design systems.
- A keen interest in integrating AI to streamline UI/UX development 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
