(LLM開発) LangChainとChatGPTを活用したRAGチャットボット作成

"LoRA-based lightweight fine-tuning: Your first step to creating a customized LLM!" This course is an introductory hands-on lecture designed so that even those encountering LLMs for the first time can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading models → applying data → training → comparing results. In a short time, you'll directly experience the flow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, gaining an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

This is a course to master the core technologies of LLM basic theory, LangChain, and RAG. You can easily learn the latest AI technologies used in practice, from LLM basics!

This is a lecture on learning text mining analysis techniques, big data analysis techniques, word frequency analysis, word cloud visualization, morphological analysis, and topic modeling analysis techniques utilizing Python and ChatGPT, covering how to utilize text mining data analysis techniques necessary for writing papers and basic application methods for research papers.

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

This course is beneficial for those who wish to learn how to use ChatGPT and acquire basic Python grammar. It's also helpful for individuals looking to learn and consolidate basic Python grammar.

This is a course for beginners in stock data analysis. Get started with stock data analysis using Python!

This is a free lecture designed to help those who are new to TEXTOM easily acquire text mining and big data analysis skills through hands-on exercises with examples, rather than focusing on fundamental theoretical explanations.

This course teaches Python-based text mining: basic theory and practice. It covers fundamental text mining data analysis for practical or thesis writing.

Instead of explanations focused on fundamental theories about 텍스톰(TEXTOM), we enable you to develop text mining and big data analysis capabilities through practical hands-on exercises.

I'm learning how to build practical AI agents using LangGraph while working on various AI agent implementation projects using LangGraph.

This lecture covers building practical RAG (Retrieval-Augmented Generation) systems while developing an AI customer service chatbot (AICC).

This video shares the experience/know-how learned while building an LLM Application with over 200,000 MAU and the supporting LLMOps environment.

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

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

Do you still code directly these days? It's now an era where even vibe coding is bothersome! Become an AI automation expert with n8n, without coding. An automation workflow design guide immediately applicable to practical work. Practice-oriented automation strategies that maximize work efficiency. Build intuitive workflows with n8n and experience business innovation.

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

We create an AI judge by combining CrewAI, facilitating LLM-based multi-agent technology, with knowledge graphs and inference systems.

You can learn everything from basic usage of generative AI to automation and creating customized AI chatbots for practical work applications all in one comprehensive course.

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

If you want to create your own AI service without coding, this course is the perfect solution. Using the Dify no-code platform, you can create high-quality AI apps with just your ideas. Instead of complex theory, it's structured around hands-on projects, allowing both AI beginners and working professionals to develop practical skills.

This is a hands-on tutorial on how to integrate with IntelliJ and develop quickly using the Model Context Protocol (MCP).

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is the technology that has come closest to AGI at this point in time. In this lecture, we explore LLM and Agent technologies from a general public perspective.