Many backend developers use Redis, but in reality, they often use it merely as a simple cache server. There are many cases where developers know the Redis data types but don't know how to apply them in practice, lack experience implementing real-world patterns like distributed locks or rate limiting, or fail to understand Redis from a backend architecture perspective. I also had the experience of pondering how to utilize Redis in a high-traffic environment while developing actual services. This is because knowing simple commands is entirely different from solving service problems with Redis. This course starts with the basic concepts and data structures of Redis and progresses through learning by implementing core patterns used in actual backend services step-by-step. In particular, you will learn how to solve the following practical problems using Redis: Caching (Cache-Aside) strategies to reduce server load, Distributed Sessions (Session Store) to share login states, Distributed Locks to solve concurrency issues, Rate Limiting to prevent API overload, and Real-time Ranking Systems (Leaderboards) for large-scale users. All hands-on exercises are conducted in a real API server environment based on Python FastAPI. Rather than just learning simple CLI commands, you will understand how Redis is used in backend systems by implementing it yourself. Through this course, you will be able to utilize Redis not just as a simple cache, but as a core tool for designing backend architecture.

This course guides you to accurately understand essential programming concepts and theories that are often neglected in the rush of implementation. By learning similar, contrasting, and related concepts together, you will master multiple ideas at once. After completing this course, you will become a developer with a solid conceptual foundation.

We'll teach you the true essence of object-oriented programming. Knowing terms and syntax like class, object, self, super(), and interface doesn't mean you understand object-oriented programming. Object-oriented programming is not simply a collection of syntax, but rather a philosophy on how to solve the problems of increasingly complex software. You can only use it properly when you understand the history and philosophy behind it. In this course, we first explain what problems object-oriented programming was created to solve, and what kind of thinking and design philosophy it embodies, independent of any specific language. Then, using Python as a tool, we gradually cover through hands-on practice how object-oriented concepts are designed and implemented in actual code. Through this course, you'll gain not object-oriented programming that merely follows syntax, but object-oriented programming that you can think through and design, and object-oriented thinking skills that remain solid even when the language changes.

Python is a versatile language. You can create applications in various fields, from website development to work automation, data analysis, and artificial intelligence development. Just as foundation work is important for building a good structure, you need solid fundamentals to create good programs. This course will firmly establish Python's basic syntax and usage through theory and practice.