Spring WebFlux + LLM Practical Implementation

AI Agent: A total integration of the latest AI technology! Implement various AI agents and learn to build your own AI agent using LangGraph.

Create your own 24-hour automated live trading bot using GPT and the Bitget API. Based on my experience working as a core talent at a major exchange, I will also share "dark" insider information and practical tips that developers without exchange experience often don't know.

Hello, I'm Woney. I specialize in one thing only: developing TradingView indicators. I believe that what's more important than "looking pretty" is having clear rules that don't waver in real trading, stable operation, and handling exceptional situations. [Indicators I Create] - Condition-based signals/alerts (alarms) - Entry/exit assistance, trend/volatility/volume-based filters - Guards to prevent over-entry/risk management (can be made optional) - Chart readability improvements (labels/lines/status windows/tables, etc.) [Development Process] 1) You provide your desired conditions "in words" → I structure them into indicator rules. 2) To avoid confusion on the chart → I organize the display methods (labels/lines/tables) together. 3) I proactively check for potential issues in real trading (duplicate signals, exceptional periods, etc.) and implement them stably. [Recommended For] - Those who have desired conditions but find implementation difficult - Those who need filters/refinement because they have too many or too few signals - Those who need readable indicators that users can understand immediately

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.

The goal is to master the complex GPT API and Python in the easiest way possible through hands-on practice. You will develop a YouTube video summarization AI using the latest ChatGPT API and implement it as a web application using Streamlit.

This course is based on the concepts learned in the Spring Framework and teaches how to implement web applications. All the learned content is summarized and a final mini-project is conducted. After completing the course, you will be able to immediately perform a real project. It contains a total of 65 lectures and 29 hours and 37 minutes of study time.

Learn the easiest way to handle AI with Spring AI. Let's learn Spring AI by building a RAG chatbot.

Don't just remain a ChatGPT user; transform into a GPT service developer with Django/Channels. Quickly grasp the core of Django/Channels with this lecture!

LLM: A pro quickly delivers core content, from essentials to practical tips!

A course that will teach you how to create a website with ChatGPT and take charge of its distribution! Learn even fine-tuning.

During the Gold Rush, it was said that it was easier to become rich by selling gold mining tools than by mining gold yourself. How about selling programs in the ChatGPT Age of Exploration?

The "How Far Can You Go with ChatGPT?" series: Creating a Stock Auto-Trading Application and Web Investment Reports!

I highly recommend Spring AI to developers using Spring Boot and React, as well as those considering the introduction of AI systems in corporate environments. This course goes beyond a simple introduction to libraries; it helps you understand the core concepts and internal structure of Spring AI, and strengthens your practical implementation skills through various hands-on examples. The course is based on Spring AI version 1.1.x and provides continuous technical support and expansion strategies to ensure you can adapt to future version upgrades. Furthermore, we expand the practical value of Spring AI technology by utilizing MCP (Model Context Protocol) to achieve cross-domain context integration, AI linkage in distributed environments, and AI architecture design suitable for enterprise environments. With the goal of building AI systems that can actually be deployed in corporate settings, this will serve as a practical guide that balances theory and hands-on experience.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

"Work automation... isn't that something only developers do?" "Even if I take an automation course, won't it be difficult without development knowledge?" No, it's not. Even if you aren't a developer and have zero development knowledge, you can apply work automation to your actual tasks. This course was created by me—someone who started as a complete beginner with no coding knowledge—for other complete beginners. Even if you are currently at a level where you've only tried asking questions to AI, you can fully understand and follow along. We will directly build automation cases actually used in the workplace, such as receiving daily automated summary reports of insightful articles and automatically detecting and announcing company anniversaries. Through this process, you will understand the 'methods of work automation' and gradually level up to build your own automation systems. Complete your first automation that can be applied to your work immediately in this course.

This course is a practical, hands-on guide to automating repetitive tasks and maximizing work productivity using ChatGPT and Python. You will learn step-by-step how to use AI to automate daily repetitive tasks such as Excel work, report writing, sending emails, and data organization. Starting as a non-developer myself, I have taught AI automation to thousands of students, and I have compiled only the methods that can be used immediately in actual business environments. This course focuses not on complex theories, but on **"automation techniques you can use right today."** 👉 The goal is to turn ChatGPT into more than just a tool, but into **your own personal work assistant (Jarvis)**.

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

Create a program using the GPT API, and even generate images and videos!

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.