Full-Stack Development with AI — Skills Plan
Planned skill map for Full-Stack Development with AI. The curriculum will be developed and released in stages.
Build responsive web products across browser UI, server routes, APIs, authentication, databases, testing, deployment, and carefully bounded AI integrations.
Potential roles: Full-Stack Engineer · AI Product Engineer
Before you start
- HTML and CSS
- JavaScript and TypeScript
- Git, terminal, and package managers
What you’ll build
- Accessible full-stack application
- AI-assisted workflow with human review
- Production deployment with monitoring
Prerequisites
PLANNED- HTML and CSS
Build the HTML and CSS knowledge needed to follow the Full-Stack Development with AI foundations.
- JavaScript and TypeScript
Build the JavaScript and TypeScript knowledge needed to follow the Full-Stack Development with AI foundations.
- Git, terminal, and package managers
Build the Git, terminal, and package managers knowledge needed to follow the Full-Stack Development with AI foundations.
Foundations
PLANNED- Browser and HTTP fundamentals
Explain how Browser and HTTP fundamentals works and where it fits in the Full-Stack Development with AI learning path.
- React components and hooks
Explain how React components and hooks works and where it fits in the Full-Stack Development with AI learning path.
- Responsive and accessible UI
Explain how Responsive and accessible UI works and where it fits in the Full-Stack Development with AI learning path.
- Node.js and server-side basics
Explain how Node.js and server-side basics works and where it fits in the Full-Stack Development with AI learning path.
- Frontend state management
Explain how Frontend state management works and where it fits in the Full-Stack Development with AI learning path.
Core Skills
PLANNED- Next.js and routing
Use Next.js and routing to implement a working capability and verify its behavior in Full-Stack Development with AI.
- Angular fundamentals
Use Angular fundamentals to implement a working capability and verify its behavior in Full-Stack Development with AI.
- Django and Spring Boot pathways
Use Django and Spring Boot pathways to implement a working capability and verify its behavior in Full-Stack Development with AI.
- REST and GraphQL APIs
Use REST and GraphQL APIs to implement a working capability and verify its behavior in Full-Stack Development with AI.
- Authentication and authorization
Use Authentication and authorization to implement a working capability and verify its behavior in Full-Stack Development with AI.
- SQL and data modeling
Use SQL and data modeling to implement a working capability and verify its behavior in Full-Stack Development with AI.
- Forms, state, and error handling
Use Forms, state, and error handling to implement a working capability and verify its behavior in Full-Stack Development with AI.
- Unit, integration, API, and end-to-end testing
Use Unit, integration, API, and end-to-end testing to implement a working capability and verify its behavior in Full-Stack Development with AI.
Advanced / Production
PLANNED- AI API integration from a server boundary
Evaluate AI API integration from a server boundary trade-offs against the performance, reliability, and safety needs of Full-Stack Development with AI systems.
- Streaming and structured responses
Evaluate Streaming and structured responses trade-offs against the performance, reliability, and safety needs of Full-Stack Development with AI systems.
- Security, privacy, and rate limiting
Evaluate Security, privacy, and rate limiting trade-offs against the performance, reliability, and safety needs of Full-Stack Development with AI systems.
- Caching and performance
Evaluate Caching and performance trade-offs against the performance, reliability, and safety needs of Full-Stack Development with AI systems.
- CI/CD, observability, and deployment
Evaluate CI/CD, observability, and deployment trade-offs against the performance, reliability, and safety needs of Full-Stack Development with AI systems.
- Accessibility and production readiness
Evaluate Accessibility and production readiness trade-offs against the performance, reliability, and safety needs of Full-Stack Development with AI systems.
Real-World Projects
PLANNED- Accessible full-stack application
Deliver a working outcome with Accessible full-stack application, then test it against the project requirements.
- AI-assisted workflow with human review
Deliver a working outcome with AI-assisted workflow with human review, then test it against the project requirements.
- Production deployment with monitoring
Deliver a working outcome with Production deployment with monitoring, then test it against the project requirements.
Career / Interview Preparation
PLANNED- Frontend and backend trade-offs
Explain your approach to Frontend and backend trade-offs, defend key trade-offs, and discuss what you learned.
- API and database design
Explain your approach to API and database design, defend key trade-offs, and discuss what you learned.
- Full-stack system design
Explain your approach to Full-stack system design, defend key trade-offs, and discuss what you learned.
- Portfolio and code review
Explain your approach to Portfolio and code review, defend key trade-offs, and discuss what you learned.
Discussion
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