By completing this course, learners will:

• Create APIs with FastAPI’s declarative syntax.

• Validate requests and responses using Pydantic.

• Build async endpoints for high throughput.

• Secure APIs with OAuth2, JWT, and API keys.

• Connect FastAPI to SQL and NoSQL databases.

• Deploy FastAPI apps to Docker, Kubernetes, or cloud.

Course Syllabus

Module 1: Introduction to FastAPI

• What is FastAPI?

• FastAPI vs Flask vs Django

• Installing FastAPI with Uvicorn

Module 2: Core Concepts

• Path and query parameters

• Request bodies and validation

• Response models and serialization

• Automatic OpenAPI docs

Module 3: Async Programming

• Synchronous vs asynchronous endpoints

• Using async/await with FastAPI

• Concurrency with Starlette

• Performance considerations

Module 4: Authentication & Authorization

• OAuth2 with JWT

• API keys and headers

• Role-based access control (RBAC)

• Securing routes and dependencies

Module 5: Database Integration

• FastAPI with SQLAlchemy

• FastAPI with Tortoise ORM and Prisma

• Connecting to PostgreSQL, MySQL, and MongoDB

• Dependency injection for DB sessions

Module 6: Advanced Features

• Middleware and background tasks

• WebSockets and real-time APIs

• File uploads and streaming responses

• Dependency injection in depth

Module 7: Testing & Documentation

• Writing unit tests with Pytest

• Using TestClient for API testing

• Auto-generated Swagger and ReDoc

• Customizing documentation

Module 8: Deployment & Scaling

• Running with Uvicorn and Gunicorn

• Dockerizing FastAPI apps

• Deploying on Kubernetes and cloud (AWS/GCP/Azure)

• Scaling and monitoring APIs

Module 9: Real-World Projects

• Task management API with FastAPI + PostgreSQL

• E-commerce backend with JWT authentication

• Real-time chat app with WebSockets

• Data science API for ML model serving

Module 10: Best Practices & Future Trends

• Project structuring and modular design

• Performance tuning and caching

• FastAPI for microservices and serverless apps

• The future of Python API frameworks

Learners will receive a Certificate of Completion from Uplatz, validating their expertise in FastAPI and modern API development. This certification demonstrates readiness for roles in backend engineering, full-stack development, and cloud-native applications.

FastAPI skills prepare learners for roles such as:

• Backend Developer (Python APIs)

• Full-Stack Developer (React/Vue + FastAPI)

• API Developer (REST & GraphQL)

• Data Scientist (model deployment APIs)

• DevOps Engineer (API deployment at scale)

FastAPI is widely adopted in startups, SaaS platforms, data science, and enterprise applications—making it one of the fastest-growing Python frameworks.

1. What is FastAPI?
A modern Python framework for building high-performance APIs with automatic validation and documentation.

2. How does FastAPI differ from Flask and Django?
FastAPI is async-ready, type-safe, and auto-generates docs, while Flask and Django are synchronous and require extensions for similar features.

3. What is Pydantic in FastAPI?
A library used for request validation, response serialization, and type safety.

4. What is the role of async/await in FastAPI?
It allows handling many concurrent requests efficiently using asynchronous programming.

5. How does FastAPI generate API documentation?
It auto-generates OpenAPI/Swagger and ReDoc docs based on type hints and models.

6. What authentication methods does FastAPI support?
OAuth2 with JWT, API keys, HTTP Basic, and custom schemes.

7. Can FastAPI handle WebSockets?
Yes, it natively supports WebSockets for real-time APIs.

8. How do you test a FastAPI app?
Using Pytest and FastAPI’s TestClient for integration and unit tests.

9. What are the benefits of FastAPI?

• High performance

• Type safety

• Auto-generated docs

• Async support

10. Where is FastAPI being adopted?
By SaaS companies, startups, AI/ML projects, and enterprises replacing Flask/Django APIs with faster, async-ready solutions.