Python Web Development: Build a Recommendation Service with Django and FastAPI

Finding the right place to eat is a challenge we face daily, making recommendation engines highly valuable. If you want to learn how to build these intelligent systems using industry-standard Python frameworks, this text-based course is for you. You will transition from basic concepts to architecting a complete, data-driven restaurant recommendation service. This course guides you through building a modern backend by combining Django's robust structure with FastAPI's asynchronous efficiency. You will learn how to organize complex data, generate personalized suggestions, and serve them reliably through clean APIs. What you'll learn: - Understand the foundational concepts of recommendation algorithms and data filtering. - Collect and clean location and restaurant data using modern Python techniques. - Configure Django to handle user authentication, database relationships, and administration. - Build high-performance, asynchronous API endpoints using FastAPI to serve your models. - Apply modern Python standards including type hints, virtual environments, and async/await syntax. - Integrate data processing and backend logic into a unified, functional application. You will start with core definitions and database design before gradually assembling your recommendation pipeline. Step-by-step written explanations and practical code snippets will guide you through connecting database management, backend APIs, and algorithmic logic. This course is designed for beginners and aspiring developers who want to transition from basic coding to building full-scale, data-driven applications. No prior experience with Django or FastAPI is required. Start reading today to build your own intelligent web services from scratch.