LLM 기초부터 최신 RAG·LangChain까지: 단 5시간 만에 LLM 기초과정 마스터!

Instead of explanations focusing primarily on fundamental theories about TEXTOM, we will equip you with text mining and big data analysis skills through practical example exercises.

This lecture is helpful for those who want to learn how to use ChatGPT and also basic Python syntax. This lecture is helpful for those who want to learn and review basic Python syntax.

- Create your own RAG chatbot in 1 day. - Practice using ChatGPT API and Langchain. - Implement LLM-based AI chatbots such as ChatGPT. - Create RAG chatbot, the current trend in the chatbot market.

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

This is a free course designed to help those new to TEXTOM easily acquire text mining and big data analysis skills through hands-on examples, instead of explanations focused on fundamental theories.

This lecture covers basic theory and practice of text mining analysis using Python. It explains basic text mining data analysis techniques required for practical work or writing papers.

This is a lecture where you will learn text mining analysis techniques, big data analysis techniques, word frequency analysis, word cloud visualization, morphological analysis, and topic modeling analysis techniques using Python and ChatGPT, as well as how to utilize text mining data analysis techniques needed for thesis writing and research paper writing methods.

AI Agent, the culmination of the latest AI technologies! Learn how to implement your own AI agent using LangGraph while implementing various AI agents.

This course covers the basic concepts and implementation of RAG (Retrieval-Augmented Generation) systems using LangChain. Participants will learn to understand the core principles of RAG and how to build and evaluate the system in practice using LangChain.

Explore the limitations of LLMs, ways to overcome them, and current research topics.

A current professional quickly delivers core content, from foundational knowledge needed for LLM to practical tips useful in the field.

Explains the necessity of LLM, its technical background, and basic concepts.

From PRD to AI-powered product recommendations, complete a real-world Next.js shopping mall project with v0, Cursor AI, and various LLMs!

Let's try creating an AI judge by combining CrewAI, which enables the implementation of LLM-based multi-agent technology, with knowledge graphs and reasoning systems.

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

This course will teach you how to create images using DALL-E. Through basic functions, a three-step prompt strategy, and hands-on image creation exercises, participants will become creative image makers.

Using Python, you will learn about the features of each service and how to implement bots through various examples, such as Telegram bot, Slack bot, KakaoTalk chatbot, and Discord bot.

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.