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FastAPI – Modern Python Backend and API Development
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FastAPI – Modern Python Backend and API Development

Course Description

A warm welcome to the FastAPI – Modern Python Backend and API Development course by Uplatz.


What is FastAPI?

FastAPI is a modern, high-performance web framework for building APIs with Python 3.7+, based on standard Python type hints. FastAPI is one of the fastest-growing web frameworks in the Python ecosystem. Known for its speed, simplicity, and production readiness, FastAPI makes it easier than ever to build scalable and high-performance RESTful APIs.

It is designed to be:

  • Fast → Built on Starlette (for web handling) and Pydantic (for data validation), making it one of the fastest Python frameworks available.

  • Easy to use → Its declarative style with type hints makes APIs quick to develop and maintain.

  • Data validation ready → Every request and response can be automatically validated against Pydantic models.

  • Production-ready → Includes built-in support for async, OpenAPI documentation, and OAuth2/JWT security.


  • How FastAPI Works

    At its core, FastAPI integrates:

    1. Starlette → Handles HTTP requests, routing, and background tasks.

  • Pydantic → Handles serialization, deserialization, and validation of request/response data.

  • Python type hints → Used to automatically generate request validation rules and API documentation.

  • Automatic docs → Built-in OpenAPI and Swagger UI docs are generated without extra configuration.


  • Real-World Applications Built with FastAPI

    FastAPI is used by startups and enterprises alike because of its speed, scalability, and simplicity. Some well-known real-world uses:

    1. Netflix → Uses FastAPI for asynchronous event-driven systems in their internal data platform.

  • Uber → Employs FastAPI for parts of its machine learning platform to handle high-throughput requests.

  • Microsoft → Uses FastAPI in their production services for building APIs at scale.

  • Explosion AI (spaCy creators) → Built the API behind spaCy, Prodigy, and other NLP tools using FastAPI.

  • Data Science & ML Teams → Widely use FastAPI to serve ML models as REST APIs, especially with frameworks like PyTorch and TensorFlow.

  • Finance & Healthcare Apps → Because of its speed and validation, it’s popular for fintech APIs and HIPAA-compliant healthcare APIs.


  • Course Description

    In this hands-on course, you’ll learn everything from the basics of routing and request handling to advanced database integration and JWT authentication. Each module is carefully structured with step-by-step lectures, coding exercises, and real-world projects to give you practical experience that you can apply immediately.

    By the end of this course, you will have built multiple working APIs - including a To-Do List App and a Book Management API - and you’ll be fully equipped to create and secure your own APIs for professional or personal projects.

    Whether you’re a Python developer, backend engineer, or a data scientist looking to deploy ML models, this course will give you the skills to confidently design, build, and scale APIs with FastAPI.


    Why Take This Course?

    There are many tutorials on FastAPI, but most leave you with incomplete knowledge or outdated practices. This course is:

    • Comprehensive – covers everything from basics to advanced concepts like JWT authentication and database operations.

  • Hands-On – you’ll build multiple real-world projects, not just toy examples.

  • Beginner-Friendly but Practical – starts from scratch yet equips you with skills that scale to professional use cases.

  • Production-Oriented – focuses on best practices like data validation, error handling, and secure authentication.

  • If you want to master FastAPI with confidence and start building real applications, this course is the most practical way forward.


    What You’ll Learn

    By completing this FastAPI course, you will be able to:

    • Set up and configure FastAPI for professional API development

  • Build and manage routes with query parameters, path parameters, and dynamic routing

  • Validate and serialize data using Pydantic models

  • Handle request bodies, form data, and user-submitted input efficiently

  • Design clean and standardized response models with appropriate status codes

  • Implement robust error handling and exception responses

  • Integrate APIs with databases and perform CRUD operations

  • Manage advanced database operations including relationships and transactions

  • Implement authentication mechanisms with Basic Auth and JWT tokens

  • Secure APIs and protect sensitive endpoints

  • Build and deploy real-world projects like a To-Do List API and Book Management API

  • Troubleshoot, debug, and optimize FastAPI applications for production


  • Requirements

    • Basic knowledge of Python programming (functions, classes, modules)

  • Familiarity with HTTP concepts (GET, POST, status codes) is helpful but not mandatory

  • A computer with Python 3.7+ installed

  • No prior web framework experience required (Flask/Django knowledge is a plus)


  • Who This Course is For

    This course is designed for:

    • Python developers who want to learn modern API development

  • Web developers familiar with Flask/Django who want to upgrade to FastAPI

  • Backend engineers building microservices or REST APIs

  • Data scientists/ML engineers deploying models through APIs

  • Students & beginners in web development who want practical, hands-on API building experience

  • Freelancers & indie hackers building MVPs and SaaS products quickly


  • FastAPI – Modern Python Backend and API Development - Course Curriculum

    Module 1: Introduction to FastAPI

    • Lecture 1: Getting Started with FastAPI

    Module 2: Routing and Parameters

    • Lecture 2: Routing and Parameters (Part 1)

  • Lecture 3: Routing and Parameters (Part 2)

  • Module 3: Data Validation with Pydantic

    • Lecture 4: Data Validation with Pydantic (Part 1)

  • Lecture 5: Data Validation with Pydantic (Part 2)

  • Module 4: Handling Requests

    • Lecture 6: Request Bodies and Form Data (Part 1)

  • Lecture 7: Request Bodies and Form Data (Part 2)

  • Module 5: Responses and Status Codes

    • Lecture 8: Response Models and Status Codes (Part 1)

  • Lecture 9: Response Models and Status Codes (Part 2)

  • Lecture 10: Response Models and Status Codes (Part 3)

  • Module 6: Error Handling

    • Lecture 11: Error Handling (Part 1)

  • Lecture 12: Error Handling (Part 2)

  • Lecture 13: Error Handling (Part 3)

  • Module 7: API Development

    • Lecture 14: Basic API Development Tutorial

  • Lecture 15: Database Integration

  • Lecture 16: Advanced Database Operations

  • Module 8: Authentication and Security

    • Lecture 17: Basic Authentication

  • Lecture 18: JWT Authentication using FastAPI

  • Module 9: Projects

    • Lecture 19: To-Do List Project

  • Lecture 20: Simple Book Management API

  • Module 10: Wrap-Up

    • Lecture 21: Common Questions and Answers on FastAPI

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