Hands-On AI Agent Fundamentals and Extension Development with a Silicon Valley Developer

The limitations of LLMs? I’ll share practical solutions to real-world problems based on RAG trial and error and operational know-how from working in Silicon Valley.

This course goes beyond basic CRUD-level database usage, helping you develop the PostgreSQL skills needed in the AI era from a practical, real-world perspective. Drawing on AI development experience in Silicon Valley, you’ll gradually learn how to design and use JSON, indexes, transactions, and pgvector in actual services, while gaining the skills to solve complex data structure and performance problems.

This course covers RPC communication techniques to maximize performance in large-scale MSA (Microservice Architecture) environments. Beyond simple gRPC practice, you will learn how to implement stable and efficient inter-service communication in real-world production environments where hundreds of microservices operate simultaneously. Based on Golang, the curriculum focuses on practical applications, including writing Protocol Buffers (proto) syntax, automated code generation and service implementation, the structure of gRPC and its advantages over traditional RPC, and performance optimization strategies. Designed to be easily understood even by non-majors or entry-level server developers, the course explains everything from the basic concepts of RPC to the internal workings of gRPC step-by-step, helping you build practical skills that can be applied immediately to real services.

This course was created to solve a common problem many people face while preparing for developer jobs: "I studied CS and data structures, but I get tongue-tied during interviews." While conducting actual interviews at companies like Naver, Kakao, and Toss, I noticed that most candidates have memorized concepts but cannot explain why those concepts are necessary or how they are applied in real-world situations. Rather than simple rote memorization, this course teaches you how to understand the interviewer's intent and provide more persuasive answers to the same questions. Whether it's the OSI 7 layers, data structures, or coding tests, we focus on why you need to know them, when they are used, and how to speak about them to receive a positive evaluation in an interview. This course is for those who want to become developers who can explain what they understand in their own words, rather than just giving the same answers as everyone else.

How will you handle exploding traffic? Learn how to build resilient and flexibly scalable architectures through practical EDA (Event-Driven Architecture) design patterns using Kafka, Spring, CDC, and Temporal. A Kakao developer shares real-world experience with clear, easy-to-follow explanations that even non-majors can understand. A practice-oriented course covering everything from real-time data flow and event processing to microservice integration!

Learn the process of building data pipelines using Apache Airflow, from the basics to practical application. Understand the core concepts and architecture of Airflow, and master advanced design patterns frequently used in the field—such as dynamic DAGs, parallel processing, distributed processing, and custom operators—through hands-on practice. Configure a practice environment using Python and Docker to develop the practical skills needed to design and operate real-world workflows.

It was created to solve the "overwhelming problem of not knowing where or how to start with Kubernetes." Based on hands-on experience operating financial infrastructure, it is designed to help you understand the actual build and operation flow rather than just simple theory. Through a learning process that covers the relationship with Docker, YAML, Pods, Deployments, and Services, learners will master Kubernetes not just as a "concept," but as a "usable skill."

This is a Redis course created with a current Kakao interviewer. It covers everything from data structure practice (String to Sorted Set) to Sentinel and Cluster configurations, helping you build design rationales that work in both interviews and real-world practice.

This course focuses on solving the problem of getting stuck in interviews and practical work due to a lack of understanding of why certain structures and configurations are necessary, rather than just teaching how to configure NGINX. Based on experience evaluating numerous candidates as an interviewer for companies like Naver, Kakao, and Toss, I explain how to describe and utilize NGINX from the perspectives of performance, scalability, and operations through hands-on practice. The core of this course is to help you develop a mindset capable of tracing traffic flow and troubleshooting problems, rather than just memorizing configuration values.

Learn the process of building essential Observability in a Microservices Architecture (MSA) environment, from the basics to practical application. You will master standardized data collection using OpenTelemetry, trace storage and search via Grafana Tempo, and visualization using TraceQL through step-by-step hands-on exercises. You will learn how to track service flows, identify bottlenecks, and analyze the root causes of failures through distributed tracing.

Systematically learn the distributed NoSQL database Cassandra, from basic concepts to practical application. Develop high-volume data processing capabilities through practice-oriented theory and hands-on exercises, including data modeling, query optimization, and cluster configuration. Even without prior database experience, you can grow into a Cassandra expert based on the know-how of a current Silicon Valley developer.

When you find yourself constantly updating Swagger documentation, aligning API specs, and repeatedly communicating with the frontend, you start to wonder, "Why am I doing the same thing twice?" I also felt similar frustrations in my professional experience, which led me to use GraphQL extensively and develop an interest in data-centric design. This course goes beyond simple GraphQL syntax; it explores the real-world problems it was created to solve, along with practical considerations like Resolver structures, the N+1 problem, and Federation. I've structured this course to help you naturally learn how to reduce communication costs between developers and design more flexible API structures.

The biggest challenges in operating batch systems that process millions of records are performance degradation and the difficulty of recovery in the event of a failure. These issues cannot be solved with simple loops or poor design. Based on my experience of reliably processing large-scale data in real-world service environments, this course covers the structure and operating principles of Spring Batch and provides design methods to achieve both performance and stability. Moving beyond simple functional descriptions, this course will help you develop fundamental data processing problem-solving skills through batch architectures that can be applied immediately in practice.

This course is for developers who want to find fundamental solutions in environments where response times slow down as traffic increases, thread pools are quickly exhausted, and bottlenecks worsen with more external API calls. It helps you look at problems from the perspective of changing the architecture itself, rather than simply scaling out servers. Through this course, you will first understand the limitations of the traditional Spring MVC "Thread per Request" model. You will examine at the code level why throughput doesn't increase even when CPU resources are available, and exactly how blocking I/O occupies system resources. Next, you will learn the concepts and standard specifications of Reactive Streams and master how to handle data streams using Reactor's Mono and Flux. Beyond simple usage, you will learn through hands-on practice how data flows start, how they are consumed, and how throughput is controlled. In particular, you will directly implement design patterns that prevent OOM (Out of Memory) or overloads using Back Pressure. Additionally, you will understand the event loop-based processing structure of Spring WebFlux and conduct comparative exercises on how Non-Blocking I/O operates during actual request processing. By placing MVC and WebFlux side-by-side to verify their structural differences, you will also establish criteria for when to choose Reactive. This goes beyond simply "learning asynchrony." You will learn how to handle more requests with fewer threads, how to maintain a stable flow in environments with high external API dependencies, and develop the design intuition to secure throughput in high-concurrency environments.

This course goes beyond simply teaching you how to use Docker as a tool; it approaches the subject from the perspective of solving the real-world dilemmas and problems encountered in professional practice. From unpredictable errors caused by differences between development and production environments, to configuration mistakes stemming from vague concepts of images and containers, and even the anxiety of "how much do I need to know to survive in the field"—this course explains it all based on firsthand experience operating financial infrastructure. Rather than just listing commands, it focuses on real-world cases: why certain structures are necessary, how to design images for easy maintenance, and how to handle containers for stable service operation. In particular, by prioritizing hands-on practice over theory, the course is designed to elevate students from simply "knowing how to use" Docker to "understanding it from an operational perspective" through visual comprehension and direct experience. This course provides practical standards and direction for those new to Docker, those who have used it but lack a clear conceptual grasp, and developers looking to take their infrastructure intuition to the next level.

Most developers are still stuck on Batch and CronJobs when it comes to data processing. However, in real-world production environments, data is generated continuously, and failing to process that flow immediately leads to latency, bottlenecks, and consistency issues. Having personally dealt with real-time recommendations, state synchronization, and event delay problems in high-traffic environments, I’ve often asked myself, "Is batch processing really the right approach for this?" This course begins with that very question. It explores how to use Apache Flink to perform computations the moment data flows, manage state securely, and produce accurate results based on Event Time—all from a practical perspective. Beyond simple theoretical explanations, you will experience how real-time stream processing systems are designed and operated through actual source code and architectures. For those who found real-time processing vague or were curious about the world beyond messaging, this course will provide a clear sense of direction.

At some point in backend development, you start to have these concerns. It's that moment when services expand and traffic increases, and you begin to feel the limitations of simple REST communication and CRUD structures. I experienced these same issues in the field and went through much trial and error balancing performance and structural complexity. The solution I chose during that process was NATS. Its simple configuration based on a single binary, ultra-low latency performance in microseconds, and the fact that it provides essential features—from Pub/Sub to Queue Groups and JetStream—without being overkill made it a very practical choice for real-world service environments. This course is not just a list of NATS features. Based on the problems I faced in practice, I explain through code and workflows why I chose NATS in certain situations and how I designed the architecture. This course is designed to help everyone—from those new to messaging systems to backend developers preparing for employment and senior developers considering better architectures—understand distributed systems and grow to the next level.

This course breaks down microservice architecture and distributed environments not as a mere list of technologies, but through the "design perspective" required in actual practice and interviews. Starting from the differences between Monolithic and MSA, it covers gradual migration strategies, Modular Monoliths, Clean Architecture, and Hexagonal Architecture step-by-step, clearly explaining why each choice is necessary and the resulting trade-offs. Furthermore, through hands-on practice, you can directly verify the intent of the structures and learn about core issues inevitably encountered in distributed environments—such as data consistency, transactions, inter-service communication, and fault tolerance—through realistic scenarios. Based on the actual questions and perspectives of a Kakao interviewer, this course aims to go beyond simple knowledge acquisition and elevate your very way of thinking about distributed systems to the next level.

This course provides a step-by-step learning path, ranging from the fundamental usage of MySQL to advanced techniques required in real-world production environments. It covers a wide range of topics, including data modeling techniques based on various case studies and practical data, evaluating the effectiveness of Foreign Key designs, analyzing Google Calendar schema DDL, and modern DDL design principles. Through this course, you will gain an in-depth understanding of how to utilize MySQL as a core system component rather than just a simple database.

Learn the SAGA transaction management technique for maintaining data consistency in distributed environments through a hands-on approach. You will configure three microservices using Spring Boot and Docker, and implement both Orchestration and Choreography patterns using Kafka and MySQL. Through this course, you will master core concepts applicable to real-world scenarios, including the operational principles of distributed transactions, designing compensating transactions, and handling fault recovery.

From a developer who only used ChatGPT to a developer who handles AI agents. Learn practical ways to maximize coding productivity using Codex's Rules, Hooks, Skills, and MCP.

The limitations of LLMs? I’ll share practical solutions to real-world problems based on RAG trial and error and operational know-how from working in Silicon Valley.

The era of building things yourself is over; now is the era of delegation. With Codex’s simple instruct-check-refine loop, turn your ideas into real results.

These days, it's become so famous that you can't afford not to know about it - Nano Banana? Gemini 3.0? In this course, you can learn to handle everything with the Gemini API.

[Sustainable AX, and How to Collaborate with AI Colleagues] Have you encountered these limitations while trying to apply AI tools to your practical work? 🙋‍♂️: "Entering commands from scratch every time is actually more of a hassle." 👨‍💻: "I feel fatigued by one-off tasks that just involve repeated copying and pasting." 🤷‍♂️: "Since I don't have development knowledge, I don't even dare to try deeper task automation." What we need right now is not just 'how to use a tool' to learn functions. It is a perspective of nurturing your own AI colleague that understands the context of your work and becomes smarter over time. We transparently reveal a practical AX (AI Transformation) guideline established by a non-developer planner through countless trials and errors in the field.

The starting point for a successful AX (AI Transformation) is not technology, but the leadership's understanding of AI. This course is designed to help executives grasp the overall flow of AI easily and clearly, while covering ways to maximize business productivity through the familiar Google Workspace and Gemini. Moving beyond mere theory, we provide 5-minute hands-on tasks for each session and a 1:1 customized online meeting (30 minutes) with AX Cody to systematically guide your company's tailored AI adoption strategy.

Have you been using LLMs only superficially? Gain a proper understanding of everything from how ChatGPT, Claude, and Gemini work to the essence of prompt design, then use those principles to collaborate with AI and create your own web novel from planning to completion. We’ll help you develop the ability to work with AI based not on “intuition,” but on “principles.”

Which AI tool should I learn first? Stop worrying now! - Rated 4.8 by 80 students ⭐️⭐️⭐️⭐️⭐️ - ChatGPT, Claude, Gemini, Genspark, NotebookLM, Gamma, Skywork, Manus, Antigravity, Claude Code, MiriCanvas, Opal, CapCut, and more - Learn the core features of over 15 tools very easily over 20 days. - Through weekly assignments, we provide a course you can "internalize" rather than just "passively listen to." - All-in-one coverage: Prompt Engineering > Image Generation > PPT & Video Creation > Vibe Coding - 4 hours of lecture videos + weekly study materials + assignment certification system

We explore how to create an AI judge by combining knowledge graphs, reasoning systems, and various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology.

AI Tech DNA Series: Core Principles of Computer Basics from an AI Perspective is an introductory course designed to help you easily understand the fundamental computer concepts necessary for the AI era. By explaining basic principles such as CPU, memory, storage, networks, and data structures through real-life analogies and an AI-focused lens, it builds the solid foundational strength needed to advance into Python, AI, security, and the cloud.

There may be people who have never taken my lecture, but no one has taken it only once. After teaching in person for so long, I have finally had the opportunity to create this online course. Since the commercialization of AI, I have produced and researched countless pieces of AI content. Based on that knowledge and experience, I have built a logical philosophy of my own and organized it into concepts that are easy for anyone to understand. For those who have been generating AI images without considering the underlying concepts, I will instill a proper foundation in you. Once you take this course, you will be able to create any AI image in the future. Have you never created an AI image before? That’s perfectly fine. You don't need any prior experience in AI image generation. By simply learning and practicing through this lecture, you can become an expert in AI content creation.

You can learn the core concepts of complex Next.js in a short time. We'll teach you only the essential practical knowledge for those learning Next.js for the first time. Captain Pangyo's new Next.js course, who has been conducting framework courses for 8 years. You can learn the coding and learning methods of "Frontend Developers in the AI Era"! 😊

We will make the entire data analysis process more accessible using chatGPT and generative AI. While gaining a better understanding of the data analysis process, you can also learn how to apply AI in practical data science.

Create a wide range of design deliverables using ChatGPT Images 2.0, including logos, product photos, mockups, banners, wedding snapshots, wedding invitations, POP displays, menus, and product detail pages. This hands-on course teaches you how to write prompts to achieve the desired results and how to structure reusable templates.

A selfish era where only those who know how to properly utilize AI can generate profit. Essential web development concepts for profitability and a realistic guide you must know to 'properly' direct AI coding agents. From the mindset of coding without writing a single line of code to realistic methods for building a product with zero budget, and even practical details on business registration and tax processing. This is an AI-driven profitable web programming guide filled with insights gained from the actual field.

Develop various features using Spring WebFlux. This course will teach you WebFlux's essential concepts and practical implementation.

Automate YouTube Shorts creation with AI!! Learn how to automatically create YouTube Shorts using n8n from scratch. We will personally build a workflow that handles everything at once: Text → Image/Music → Video Creation → Uploading. Practice includes distinguishing between test/production modes and tips for saving costs. By the end of the lecture, you will complete 3 automation templates that can be used immediately. We will learn step-by-step, starting from node placement, so you can follow along even without coding knowledge. Join us in automating AI YouTube Shorts production!

You can implement hands-on practice of infinitely generating cryptocurrency trading signals automatically using ChatGPT and Python, and backtesting and validating them. Additionally, you can learn how to combine all the strategies automatically generated by AI into a single strategy and apply it to actual trading.

While your colleagues are already working with Claude Code, are you still doing all of this manually? Don’t worry! Take this course, and you too will become a vibe-coding master.

AI Workflow Automation + Passive Income Generation in Just One Click!!! The ultimate tool for workflow automation, Make—were you hesitant to start because of its complex settings and features? Implement the automation of your dreams yourself with step-by-step lessons that even beginners can easily follow.