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Python
15 hours
Backend on FastAPI from scratch
From an empty folder to a public HTTPS URL of your API on the internet. Not another hello-world but a real backend: registration, a database with migrations, protected endpoints, tests, and auto-deploy — something you can put on your resume.
- An API with PostgreSQL, Alembic migrations, and Swagger docs out of the box
- Registration, JWT tokens, and endpoints isolated from other users' data
- Tests with transaction rollback, a Docker container, and auto-deploy to free hosting
26 lessons
Certificate on completion
The course is part of premium — together with the other advanced courses, the AI assistant and certificates.
main.py
@app.get("/users/{id}")
async def get_user(id: int) -> UserOut:
user = await repo.get(id)
return user
$GET/users/7
# Pydantic validates and coerces the types
200 OKapplication/json
{
"id": 7,
"name": "Ada",
"is_active": true
}
✓ Swagger docs out of the box
What changes after the course
Now
After the course
I know Python syntax but have no idea how to turn it into a real web service
You build a REST API with FastAPI: routes, request validation and auto docs
Data lives in lists and dicts and disappears after a restart
You store data in PostgreSQL and version the schema with Alembic migrations
Anyone can hit my endpoint — I've only heard about auth
Registration, JWT tokens and endpoints protected from other users
The project sits on my laptop and "works on my machine"
You package the project in Docker and set up auto-deploy — the API is available to anyone by a link, not just on your machine
Course program
Each lesson is short theory on live examples plus practice in the trainer with auto-checking. Nothing to install: Python runs right in the browser.
About the course
What is a backend: client, server, API
Installing FastAPI and the first endpoint
Path and query parameters
Pydantic and request body
HTTP under the hood: method, status, headers
Response models and status codes
PostgreSQL in Docker
SQLAlchemy: model, engine, session
Database session via Depends
CRUD endpoints backed by a real DB
Alembic: schema migrations
Bloated main.py: extracting routes
Layers: routes / services / repositories
Config via pydantic-settings
Password hashing: bcrypt
Registration and login
JWT tokens
Protecting endpoints via Depends
First pytest test with TestClient
Test database with transaction rollback
What and how to test in an API
What a container actually is
Dockerfile for FastAPI
Deploying to Render
Course complete
How the learning works
01
Read a lesson with live examples
Theory without filler: every code example can be run and edited right in the browser, with the result shown instantly.
02
Solve tasks in the trainer
You write code and the answer is checked automatically against a set of tests. No local environment setup.
03
Stuck — the AI mentor helps
The built-in assistant points out where the error is and nudges you toward the solution without giving it away.
Who is this course for
Finished Python basics and want a profession
You know functions, lists and dicts but don't see how a real interview-ready backend grows out of them.
A frontend dev tired of waiting for someone else's API
You want to bring up the server, the database and the endpoints yourself instead of asking a backender for one more route.
An analyst or tester moving into development
You already write Python scripts and want a real service with a database, auth and deploy on your resume.
You'll need Python basics — variables, functions, lists and dicts. If you don't have them yet, start with the free "Python Basics" course, then come back.
A certificate you can verify
Complete all the lessons and get a named certificate of completion. You can add it to your resume or your LinkedIn profile.
Your name and the course title
QR code and verification link
What students say
Marina
Spent six months on Python video courses. Everything made sense in lectures, but sitting down to write code from scratch never worked. Here you write from task one. On harder tasks I'd get stuck, but premium unlocks reference solutions, and I'd compare my janky code to the canonical version line by line. A month in, I wrote a script at work that builds a report from 30 CSV files.
Artem
Bombed a tech interview on a simple dictionary task, brain just shut down under stress. Worked through interview tasks from Yandex and Avito in the trainer, at the next interview I got almost the same problem and had an offer within a week.
Katya
Moved from manual QA to development, and toy tasks about factorials and Fibonacci were driving me crazy. In the trainer it's JSON parsing, CSV processing, API work, exactly what I do at my job, just without deadlines and the fear of breaking prod.
One premium — all courses at once
You're buying not a single course but the whole Python Academy premium: the advanced courses and every trainer feature.
- Access to advanced Python courses
- Unlimited hints from AI Assistant
- Access to tasks from top company interviews
- Access to reference solutions for tasks
- Certificate of successful completion of Python tasks in the trainer
$ 24,90
6-month access
Secure payment by Russian card via YooKassa or by international card via Stripe. Access opens right after payment.
Frequently asked questions
I just finished a basic Python course — is this really for me?
Yes, this course is designed exactly for that point: beyond basic functions, classes, and loops, it doesn't assume anything. Backend, HTTP, databases, JWT, and Docker — we introduce all of these from scratch, with a short explanation right in the lesson where each new term first appears.
What will I have at the end?
A public URL like https://<your-app>.onrender.com pointing at your own API on the internet. Anyone can register, log in, and create a task through it — a real backend, not a learner's hello-world. Plus a GitHub repository where each step of the course sits under its own git tag — perfect to share on your resume or in interviews.
How long does the whole course take?
Around 15 hours of reading and coding — that's seven or eight evenings of about two hours, or three to four focused weekends. Every lesson is self-contained — you can pause and resume any time, since the code state for each step is always on GitHub under its own tag, ready to clone and continue from.
What should I install upfront?
Python 3.11+, Docker, and any IDE with Python support (VS Code, PyCharm — whatever you prefer). All libraries (FastAPI, SQLAlchemy, Alembic, pytest, and the rest) we install as we go. If Docker feels intimidating — there's a dedicated lesson explaining containers in plain terms, and you don't need to touch Docker until then.
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