Full Stack Development — End-to-End Web App Engineering
Build production-ready web applications with a Python-first backend (FastAPI & Django) and modern React/Next.js frontends. Deploy to cloud, automate CI/CD, and embed AI services — tailored labs for Finance and Energy domains.
Program Snapshot
- • Frontend: React, Next.js, Tailwind, TypeScript
- • Backend: FastAPI (primary), Django, PostgreSQL
- • DevOps: Docker, GitHub Actions, AWS/Azure deployment
- • AI Integration: LangChain/OpenAI, model microservices
Overview
A practical, project-driven program emphasizing Python backend development (FastAPI + Django), modern frontend engineering (React/Next.js), secure APIs, scalable deployments, and integrating ML/AI services into full-stack products. Great for developers, data engineers, and solution architects who want production skills.
Who should join
Developers, data practitioners, and engineers aiming to ship production apps that include data & AI components.
What you'll deliver
A deployable full-stack app, CI/CD pipeline, documentation, and a GitHub portfolio project.
Prerequisites
Basic programming in Python or JavaScript; recommended: familiarity with Git and SQL.
Curriculum Snapshot
Modular curriculum aligned to real projects. Emphasis on practical labs, security, testing, and production readiness.
Frontend Track (React & Next.js)
- HTML, CSS, JavaScript to TypeScript migration
- React fundamentals, hooks, and state management
- Next.js — SSR, SSG, API routes, and edge functions
- Tailwind CSS, component libraries, accessibility
- Testing with Jest/React Testing Library
Backend Track (FastAPI primary & Django)
- Designing RESTful & GraphQL APIs
- FastAPI: async endpoints, dependency injection, validation
- Django for rapid app development and admin interfaces
- PostgreSQL, SQLAlchemy/ORM, migrations, and indexing
- Authentication (JWT, OAuth2), rate limiting, and security best practices
DevOps & Deployment
- Containerization with Docker & docker-compose
- CI/CD with GitHub Actions — tests, linting, build, deploy
- Cloud deployment: AWS ECS / EKS, Azure App Service, or serverless options
- Secrets management, environment configs, and monitoring
Data & AI Integration
- Expose ML models as microservices (FastAPI + MLflow)
- Embed LangChain/OpenAI for conversational features
- Inference optimization, caching, and batching
Quality & Observability
- Testing: unit, integration, e2e (Cypress/Playwright)
- Logging, tracing (OpenTelemetry), and metrics (Prometheus/Grafana)
- Performance profiling and cost optimization
Hands-on Labs & Projects
Project-first labs — each produces a deployable app and GitHub portfolio entry.
Finance — Portfolio Tracker App
React frontend + FastAPI backend; integrates public market data, supports user auth, and shows P&L charts. Deployable with Docker and GitHub Actions.
Energy — IoT Renewable Monitoring Dashboard
Next.js dashboard with Django backend for device management, real-time charts via WebSockets, and Azure/Edge deployment options.
AI Integration — Smart Chatbot
Build a LangChain-backed assistant served by a FastAPI microservice that connects to document stores; deploy with Docker & monitor usage.
DevOps — CI/CD Pipeline Project
Full GitHub Actions pipeline implementing test stages, container builds, and automated deployments to AWS/Azure with rollback strategies.
How this Course Connects — Comparison Table
| Focus Area | Full Stack Development | AI Engineering | ML Products & Platforms |
|---|---|---|---|
| Primary Goal | Build deployable full-stack apps & APIs | Deploy, monitor & automate ML systems | Productize ML models as reusable services |
| Key Tools | React, FastAPI, Django, PostgreSQL, Docker | Databricks, MLflow, LangChain | Feast, Vertex AI, MLflow, Databricks |
| Deliverable | End-to-end web application | Production-grade ML pipeline | ML API or multi-tenant platform |
| Integration | Hosts ML microservices and UI | Provides model artifacts for apps | Scales ML services across customers |
Certification & Outcomes
Complete the projects and assessments to earn the Yukti Certified Full Stack Developer badge. Graduates receive a portfolio-ready GitHub repository, deployment templates, and interview prep resources.
Self-paced
Recorded lessons, projects, and lifetime access to materials.
Cohort (Instructor-led)
10-week live cohort with mentorship, code reviews, and capstone feedback.
Enterprise
Private cohorts, tailored projects, and integration into company pipelines.
Enroll or Request a Brochure
Tell us about your team or interest and we'll send a tailored brochure, schedule, or enterprise proposal.