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Full-Stack AI Engineer Blueprint (Beginner to Advanced)

This guide extends the ML journey in this repository with software engineering depth, so you can move from training models to shipping complete AI products.

Think of it as a practical "build and deploy" companion to the core ML roadmap.

Naming note: Topic labels such as Module 01 in this blueprint are steps inside this guide only. They are not the same as this repository’s numbered folders (00-prerequisites25-generative-ai-llms). When this file says “pair with core ML modules,” it always means those repo folders.

In-repo lesson chapters: Step-by-step chapters live under PH2. Read the matching chapter for each phase, then return here for deliverables and external free links.


Why This Blueprint


How to Study This Path

  1. Follow phases in order.
  2. Build the deliverable at the end of each phase.
  3. Pair this with core ML modules from the main roadmap.
  4. Use AI assistants for speed, but keep core reasoning and debugging manual.

Phase A: TypeScript Foundations

In-repo lesson: Phase A: TypeScript foundations

Outcome

Write clean, type-safe TypeScript and reason confidently about types.

Module Coverage

Portfolio Deliverable

Build and publish a small TypeScript utility library with tests and examples.


Phase B: Node.js, Express, and API Core

In-repo lesson: Phase B: Node and APIs

Outcome

Understand server fundamentals and build secure REST APIs.

Module Coverage

Portfolio Deliverable

Ship a user-management backend with role-based access and refresh-token authentication.


Phase C: Database and SQL Mastery

In-repo lesson: Phase C: SQL and databases

Outcome

Design scalable relational schemas and write reliable SQL for real applications.

Module Coverage

Portfolio Deliverable

Create an ERD-backed SQL project with migration scripts and documented query examples.


Phase D: Prisma + Next.js Full-Stack Build

In-repo lesson: Phase D. Prisma and Next.js

Outcome

Build production-style applications with clean backend architecture and modern frontend patterns.

Module Coverage

Portfolio Deliverable

Build a full-stack content platform with authentication, moderation flow, and analytics.


Phase E: Advanced Backend Engineering

In-repo lesson: Phase E: Advanced backend

Outcome

Move from "feature-complete" to "production-reliable."

Module Coverage

Portfolio Deliverable

Develop a domain backend (for example healthcare booking) with payments and automation jobs.


Phase F: Advanced Frontend Engineering

In-repo lesson: Phase F: Advanced frontend

Outcome

Build complex, maintainable frontends with role-aware dashboards and data-heavy UIs.

Module Coverage

Portfolio Deliverable

Create a multi-role admin dashboard with analytics cards/charts and advanced table workflows.


Phase G: Cloud, Containers, and Delivery

In-repo lesson: Phase G: Containers and delivery

Outcome

Containerize services and run multi-service systems with confidence.

Module Coverage

Portfolio Deliverable

Run a composed stack (frontend + API + database + reverse proxy) with reproducible local deployment.


Phase H: AI Integration for Full-Stack Products

In-repo lesson: Phase H: AI integration

Outcome

Design AI features that are useful, grounded, and production-aware.

Module Coverage

Portfolio Deliverable

Ship an AI assistant feature with retrieval grounding, monitoring hooks, and fallback/error handling.


Bonus Tracks


Free Resources by Phase

Use these free resources alongside each phase. They are practical, well-maintained, and beginner-friendly.

TypeScript (Phase A)

Node.js and APIs (Phase B)

SQL and Databases (Phase C)

Prisma and Next.js (Phase D and F)

Backend Reliability and Security (Phase E)

Containers and Cloud (Phase G)

AI Product Integration (Phase H)


Pairing with This Repository's ML Roadmap

For balanced growth, run both tracks:

If you complete both tracks, you will not only train models, but also design and ship AI systems that real users can trust.