Great for freshersIdeal for career switchers

Python Backend Engineering

Go from Python basics to production backend engineer in 14 weeks.

Duration: 14 weeks
Duration
Sessions: 21
Sessions
Labs: 14
Labs
Projects: 3
Projects

What You'll Be Able To Do

After completing this course, you will confidently:

Write production-quality Python using advanced patterns including decorators, generators, async/await, and type hints
Design and build RESTful APIs with FastAPI including input validation, dependency injection, and OpenAPI documentation
Model relational databases with PostgreSQL and manage schema evolution using Alembic migrations
Implement authentication and authorization using JWT tokens, OAuth2 flows, and role-based access control
Build asynchronous task processing pipelines with Celery and Redis for background jobs
Design caching strategies with Redis to reduce database load and improve response times
Write comprehensive test suites using pytest with fixtures, mocking, and integration test patterns
Containerize and deploy Python applications with Docker and Docker Compose for reproducible environments

What You'll Build

Real portfolio projects that showcase your skills to employers.

Multi-Tenant SaaS API

Build a multi-tenant API with FastAPI featuring tenant isolation, JWT authentication, role-based access control, rate limiting, and pagination. Deploy with Docker Compose including PostgreSQL and Redis.

FastAPIPostgreSQLRedisDockerSQLAlchemyJWT

Interview value:

Multi-tenancy is a common backend architecture question in interviews and demonstrates understanding of data isolation and security.

E-Commerce Order Processing System

Design an order processing system with Django REST Framework featuring inventory management, payment state machine, email notifications via Celery, and an admin dashboard.

DjangoDjango REST FrameworkPostgreSQLCeleryRedis

Interview value:

E-commerce systems involve complex state management, concurrency, and transactions — topics frequently explored in system design interviews.

Real-Time Notification Service

Build a notification microservice that supports email, SMS, and push channels. Implement priority queues, retry logic with exponential backoff, delivery tracking, and WebSocket real-time updates.

FastAPIWebSocketsCeleryRedisPostgreSQLDocker

Interview value:

Demonstrates asynchronous programming, queue design, and reliability patterns that are core to backend engineering interviews.

Course Curriculum

14 weeks of structured, hands-on learning.

1Python Advanced Patterns

Decorators — function and class decorators, decorator factories
Generators, iterators, and context managers
Type hints, dataclasses, and Pydantic models
Virtual environments, dependency management, and project structure

Lab: Python Advanced Patterns — Library UtilitiesDocker Lab

2FastAPI Fundamentals

FastAPI application structure and routing
Request validation with Pydantic — body, query, path parameters
Dependency injection and middleware
Automatic OpenAPI documentation and Swagger UI

Lab: Build a CRUD API with FastAPIDocker Lab

3PostgreSQL & SQLAlchemy

Relational database design — normalization, indexes, constraints
SQLAlchemy ORM — models, relationships, eager/lazy loading
Alembic migrations — auto-generate, upgrade, downgrade
Connection pooling and query optimization

Lab: Database Design & SQLAlchemy ModelsDocker Lab

4Authentication & Authorization

JWT tokens — access tokens, refresh tokens, and token rotation
OAuth2 flows — authorization code, client credentials
Password hashing with bcrypt and secure session management
Role-based access control (RBAC) and permission middleware

Lab: JWT Auth System with Role-Based AccessDocker Lab

5Django & Django REST Framework

Django project structure, settings, and app architecture
Django ORM — models, managers, querysets, and raw SQL
Django REST Framework — serializers, viewsets, and routers
Django admin customization and management commands

Lab: Django REST API with Admin DashboardDocker Lab

6Redis Caching & Session Management

Redis data structures — strings, hashes, lists, sets, sorted sets
Caching patterns — cache-aside, write-through, TTL strategies
Session management and rate limiting with Redis
Redis pub/sub for real-time messaging

Lab: Redis Caching Layer for API PerformanceDocker Lab

7Celery & Asynchronous Tasks

Celery architecture — workers, brokers, result backends
Task design — retries, exponential backoff, dead-letter queues
Periodic tasks with Celery Beat
Monitoring Celery with Flower dashboard

Lab: Async Task Pipeline with Celery + RedisDocker Lab

8Testing & Quality Assurance

pytest fundamentals — fixtures, parametrize, markers
Mocking external services and database interactions
Integration testing with TestClient and test databases
Code coverage, linting with ruff, and type checking with mypy

Lab: Comprehensive Test Suite for REST APIDocker Lab

9Error Handling & Structured Logging

Custom exception hierarchies and global error handlers
Structured logging with structlog — JSON output, correlation IDs
Health check endpoints and readiness probes
API versioning strategies and deprecation workflows

Lab: Error Handling & Logging MiddlewareDocker Lab

10Async Python & WebSockets

Python asyncio — event loop, coroutines, tasks, and gather
Async database queries with async SQLAlchemy
WebSocket connections with FastAPI for real-time features
Server-Sent Events vs WebSockets — trade-offs and use cases

Lab: Real-Time Notifications with WebSocketsDocker Lab

11File Handling, Uploads & Background Processing

File uploads with FastAPI — streaming, validation, virus scanning
S3-compatible object storage with MinIO
PDF and CSV generation for reports
Background job patterns for long-running operations

Lab: File Upload Service with S3 StorageDocker Lab

12Docker & Deployment

Dockerfile best practices for Python applications
Docker Compose for multi-service local development
Environment configuration with .env files and secrets management
Gunicorn and Uvicorn — production ASGI/WSGI server configuration

Lab: Dockerize Full Application StackDocker Lab

13API Design Patterns & Security

REST API design best practices — resource naming, pagination, filtering
CORS, CSRF, and security headers
Input sanitization and SQL injection prevention
API documentation standards and Postman collection generation

Lab: Production API Security HardeningDocker Lab

14Capstone Project & Interview Preparation

End-to-end capstone project execution and code review
Backend engineering interview question patterns
System design fundamentals for backend interviews
Portfolio presentation and resume optimization

Lab: Capstone — Multi-Tenant SaaS APIDocker Lab

Hands-On Labs Included

You build these yourself — guided exercises with real tools, not passive demos.

Build a CRUD API with FastAPI

Docker Lab

2 hours

FastAPIPythonPydantic

Database Design & SQLAlchemy Models

Docker Lab

2.5 hours

PostgreSQLSQLAlchemyAlembic

JWT Auth System with Role-Based Access

Docker Lab

2 hours

FastAPIJWTbcrypt

Redis Caching Layer for API Performance

Docker Lab

2 hours

RedisFastAPIDocker Compose

Async Task Pipeline with Celery + Redis

Docker Lab

2.5 hours

CeleryRedisPython

Comprehensive Test Suite for REST API

Docker Lab

2 hours

pytestFastAPI TestClientDocker

Who Is This For?

Freshers & Graduates

Just graduated or finishing your degree? This course gives you the practical skills and portfolio projects that campus placements and entry-level interviews demand.

Career Switchers

Moving from another domain into tech? The structured curriculum and real-world projects bridge the gap between theory and what employers actually look for.

Ideal If You Are:

Fresh graduates who know basic Python and want to become backend engineers
Frontend developers who want to add backend skills
Career switchers from other languages (Java, PHP, Ruby) moving to Python
Data analysts or scientists who want to build production APIs

Prerequisites

Basic Python programming (variables, functions, loops, classes)
Understanding of HTTP and REST concepts
A laptop with at least 8 GB RAM and Docker Desktop installed
No prior framework experience required

Career Support Included

We don't just teach you — we help you land the job.

Mock Interviews

Practice with real-world interview scenarios. Get feedback on technical depth, communication, and problem-solving approach.

Resume Review

One-on-one review sessions to craft a resume that highlights your projects, skills, and achievements the right way.

Portfolio Coaching

Guidance on presenting your course projects as professional portfolio pieces that stand out to hiring managers.

LinkedIn Optimization

Tips and templates to optimize your LinkedIn profile so recruiters find you and reach out.

Learn from Industry Practitioners

Our instructors are working professionals who build production systems daily. They bring real-world experience, battle-tested patterns, and the kind of practical insight that textbooks can't teach.

Course Details

Format	Live Online
Duration	14 weeks
Schedule	21 sessions
Batch Size	Max 15 students
Certificate	Yes, on completion
Lab Setup	Docker-based (runs on your laptop)
Price	Enquire for pricing

Frequently Asked Questions

Will I get a job after completing this program?

Our curriculum is designed by a principal architect with 20+ years of hiring experience. The program produces engineers with the skills hiring managers look for — proper testing, error handling, database design, and clean API architecture. While we cannot guarantee placement, graduates are well-prepared for Python backend interviews.

Do I need experience with FastAPI or Django?

No. We teach both frameworks from scratch. You need basic Python knowledge (functions, classes, loops), but all framework concepts are taught from the ground up.

Should I learn FastAPI or Django?

We teach both because the job market demands it. FastAPI dominates in modern API development and microservices. Django is widely used in established companies. Understanding both makes you a more versatile backend engineer.

Is this course enough to become a full-stack developer?

This course focuses on backend engineering. If you want full-stack skills, consider our Full-Stack Python + React program which covers both frontend and backend. However, strong backend skills alone are sufficient for many well-paying roles.

How much Python do I need to know before starting?

You should be comfortable with Python basics — variables, functions, loops, lists, dictionaries, and basic class syntax. If you can write a function that takes a list and returns filtered results, you are ready.

What if I miss a live session?

All sessions are recorded and available on the student portal within 24 hours. The instructor and TAs are available on Slack for questions between sessions.