In the Age of AI, Developers, Become Architects! — Principles and Practice of Software Architecture Design

Uncover true value in the age of data! 📊 Designing applications focused on data has now become essential. Develop the insight and skills your company wants with the latest trends and practical case studies. Start now with efficient data processing and design secrets! Your next step, leap into the data-driven world!

Software quality is a habit! This course will teach you how to become the best programmer that companies want.

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.

A comprehensive course covering AI-era-proof Silicon Valley internships, 30 big-tech system designs, and hands-on open-source contributions. Using real-world cases from Netflix, Tesla, Meta, Tinder, and other big tech companies, you’ll design and scale 30 practical system designs. Finally, you’ll design your own service from architecture to database to scaling.

In the cloud field, we deliver the overall background of Microservice Architecture (MSA), a hot keyword, along with various architecture patterns, application types, and legacy conversion methods through real-world insights.

Learn database design systematically across three levels—conceptual, logical, and physical—and strengthen your skills through a practical, project-based e-commerce store. Gain hands-on expertise through modern design techniques and the latest trends.

Alongside reading, writing, and arithmetic, computational thinking is a skill that everyone living in the AI era must possess. Computational thinking can be simply defined as thinking like a programmer or thinking like a computer scientist. This course faithfully reproduces an actual university semester-long course and covers essential content for those encountering programming for the first time or beginners planning to major in computer science. It also helps non-computer science majors and people with humanities backgrounds develop the ability to communicate easily with professional programmers. Even in an era when we need to learn prompting for AI vibe coding, this course helps learners develop the ability to give AI more accurate and effective instructions through computational thinking.

In an era where AI writes code for us, the value of a "true architect" who can see through and control the macroscopic framework of a system becomes overwhelmingly higher. This course digs into the essence of low-level networks and TCP/UDP sockets hidden behind frameworks, cultivating the ability to design robust core engines that never crash even in the face of millions of traffic hits and large-scale data. Go beyond being a coder who blindly repeats copy-pasting, and leap forward to become an irreplaceable master who directs and controls AI with clear, system-level solutions.

Through this course, you can acquire the concepts and practices of Information Strategic Planning.

Solve the common codes, category hierarchies, history tracking, soft deletes, statistics, dynamic design, JSON utilization, and more that you inevitably encounter in real-world design through nine core patterns. This goes beyond simple theory, incorporating practical know-how proven across numerous projects and criteria for making the right choices in different situations. Become a true design expert who can confidently design for any requirement.

Because you never know when or how software will grow, you must always be prepared to scale it continuously. This presents one direction for doing so.

How does the architecture change when an LLM is integrated into an existing backend? Going beyond simple LLM API calls, this introductory system design course helps you understand the core components of AI services—such as Model Routers, LLM Gateways, and Vector DBs—and progressively design operational AI service architectures, including RAG and AI Agents. It helps those who want to build their own LLM-based AI services quickly learn the design process.

Regardless of the field! This is a lecture that covers the core fundamentals that developers must know in practice in an easy + code-oriented way. I highly recommend this lecture to all junior developers and job seekers who want to grow.

Along with reading, writing, and arithmetic, computational thinking is a skill that everyone living in the AI era must possess. Computational thinking can be simply defined as thinking like a programmer or a computer scientist. This course faithfully reproduces an actual university semester-long course and covers essential content for people encountering programming for the first time or beginners planning to major in computer science. Through this course, people without a background in computer science or with a humanities background can also develop the ability to communicate easily with professional programmers. Even in an era when learning prompts for AI vibe coding is necessary, this course helps you develop the ability to give AI more accurate and effective instructions through computational thinking.

I have created an 'AWS Intermediate/Practical' course that is easy to understand even for non-majors and can be applied immediately in the field!

You can solve design problems by writing code in a formatted way. You can understand code or patterns written by other programmers.

It explains almost everything surrounding the cloud in an easy-to-understand manner. If you listen to it before the actual practice, you will be able to understand development or infrastructure cloud well.