Builder
Engineering
Available on request
FastAPI: Building Production APIs in Python
From first endpoint to a documented, tested, deployed API serving AI models in production.
Validation, authentication, streaming, testing and deployment, ending with an API you would put your name on.
- Duration
- 7 days, 40 contact hours
- Cohort size
- 8 to 14 participants
- Delivery
- In-house, Online, Blended
- Languages
- Arabic, English
Who it is for
Python developers, backend engineers, data teams shipping models.
What people leave able to do
- Build a complete REST API with validation, authentication and documentation
- Serve an AI model behind a production-grade API
- Handle async workloads, streaming responses and long-running tasks
- Secure, test and version an API properly
- Deploy with Docker and monitor it in production
Modules
- 01 FastAPI fundamentals and async Python
- 02 Pydantic and request validation
- 03 Routing, dependencies and project structure
- 04 Database integration with SQLAlchemy
- 05 Authentication, JWT and API keys
- 06 Serving AI models and streaming responses
- 07 Background tasks and job queues
- 08 Testing with pytest
- 09 Error handling, logging and observability
- 10 Rate limiting and security hardening
- 11 Docker and deployment
- 12 Capstone: a deployed, documented AI-serving API
Prerequisites
Solid Python: functions, classes, packages.
Start with a short call
Fifteen minutes to understand what your team does and what you want to change. If training is not the right answer, I will say so.