The goal AI Fullstack Engineer training is to train engineers who can build, ship, and maintain modern web applications with AI features across frontend, backend, APIs, data, and deployment. The curriculum emphasizes hands-on project work, production practices, and AI-assisted development rather than theory alone.
Curriculum outline
- Engineering foundations Programming fundamentals: Python and JavaScript.
Git, GitHub, CLI, debugging, and code organization.
HTML, CSS, responsive design, accessibility.
Data structures, algorithms, and problem-solving basics.
- Modern frontend JavaScript ES6+, async programming, DOM, and browser APIs.
React fundamentals, component architecture, state management, routing.
UI design systems, Tailwind CSS or similar, and frontend testing.
Building polished dashboards, forms, and customer-facing interfaces.
- Backend engineering Node.js or Python backend development.
REST APIs, authentication, authorization, middleware, logging.
Database design with PostgreSQL or MongoDB.
Background jobs, caching, file uploads, and error handling.
- AI application layer Generative AI fundamentals, LLM concepts, prompt engineering.
API integration with OpenAI or other model providers.
Retrieval-augmented generation, embeddings, vector databases.
AI safety, hallucination handling, evaluation, and guardrails.
- Fullstack deployment Environment variables, secrets, CI/CD basics.
Docker fundamentals and cloud deployment.
Monitoring, analytics, tracing, and performance optimization.
Production readiness: testing, rollbacks, and incident basics.
- Product and delivery skills Agile workflow, sprint planning, tickets, PR reviews, and collaboration.
Reading PRDs, estimating work, and communicating tradeoffs.
AI-assisted development workflows with Copilot/ChatGPT-style tools.
Working with stakeholders and shipping incremental releases.
Capstone projects: Students will do one or more of the following projects. AI-powered internal knowledge assistant. Resume screening and candidate-matching platform. Customer support copilot. Workflow automation dashboard for sales or operations. AI research and summarization tool.
Recommended hiring bar:
By the end of the program, a strong candidate should be able to:
Build a complete fullstack app from scratch. Integrate an LLM into a real workflow. Debug frontend, backend, and AI issues. Deploy and monitor a production app. Work in a team using Agile and Git workflows.