Future of Developers! AI Vibe Coding Part 1 - Create Your Own MCP Server with Cursor

We will learn step by step from the basic concepts of LLM (Large Language Model) to how to fine-tune the Llama 2 model, a high-performance LLM, on the dataset of your choice.

From the basics of deep learning natural language processing to the latest models such as Transformer and BERT, learn the principles and utilization methods of deep learning natural language processing (NLP) through various examples and practical code implementations.

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

This course will teach you the core theories of deep learning and how to implement deep learning code using the latest TensorFlow 2.0.

Learn all the steps from A to Z required to create and operate a cryptocurrency automatic trading coin bot. (Basics of using exchange APIs, deployment using AWS) You can also learn investment strategies (such as using Kimchi Premium) that can generate risk-free returns of around 10% per year by utilizing the structural characteristics of the cryptocurrency market.

This course covers work automation using MCP (Model Context Protocol) via diverse case studies: Playwright crawling, Figma design, Notion data organization, Excel data analysis.

This is a lecture to build an AI portfolio by doing a clone project of airbnb data science team's Amenity Detection project, an excellent TensorFlow utilization case, and organizing the experience on a GitHub blog.

This course teaches you how to implement deep learning papers by implementing the YOLO (You Only Look Once) paper from scratch using TensorFlow 2.0.

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

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

This lecture teaches various business automation methods using ChatGPT (Excel, PPT, crawling, image processing) and Python basics for business automation. Experience in advance the changed future that ChatGPT will create.

A course to learn website crawling methods using ChatGPT. Get a preview of the transformed future ChatGPT will create.

This is a course to learn the concepts and usage methods of the LangChain library, and to build your own ChatGPT using the LangChain library.

This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

Through AI company reviews, we examine how AI technology will change our present and future through various cases. By examining the necessary elements for carrying out AI projects, we prepare for the upcoming AI Transformation.

Data Science(DS) & Artificial Intelligence(AI) job role analysis, plus a learning & employment roadmap for building a career in these roles.

This is a lecture on creating an automatic stock trading bot using the IBK Investment & Securities Xing API. Create your own automatic stock trading bot that trades automatically 365 days a year.

This course covers data analysis using ChatGPT and Pandas utilization. Get a preview of the changed future ChatGPT will create.

A course to learn deep learning paper implementation skills, implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper from scratch with TensorFlow 2.0.

This lecture teaches how to create diverse quant investment strategies using ChatGPT. Use ChatGPT to build your own quant investment strategy.

In just 2 hours of hands-on practice, we build a local LLM with RAG-based QA system using the Docker + ollama + R2R framework. (Internal/in-house QA systems, personal portfolios, AI-powered work capabilities, and even commercial services are possible.)

What should be done when building a generative AI or LLM-based RAG (Retrieval-Augmented Generation) system, but the desired performance isn't achieved and there's no suitable solution? This lecture presents methods to improve RAG performance based on Cognitive Load theory. Through this lecture, you will understand the limitations of LLM context windows and learn how to effectively manage cognitive load in RAG systems. It is a practical-level theoretical lecture covering Chunk size and structure design, high-quality Chunk generation techniques, dynamic optimization, performance evaluation, and practical techniques.

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

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

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

This course teaches you the know-how of the entire process, starting from a single idea, through planning, design, development, and up to app release on each platform. Start developing your own monetization app right now.

Perfectly master the working process of MCP by creating a TodoList with Claude and IntelliJ.

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

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.

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

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

Don't know coding? OK! Turn your ideas into real revenue in just 4 weeks. Using AI and the latest tools, create websites and apps simultaneously and connect them directly to services.

The Latest Trend in Generative AI, AI Agents! How to Stay Ahead with Cursor, which handles all development tasks, and MCP, which expands functionality!

AI writes on my Slack and Notion for me? Work smarter with MCP that surpasses the limitations of existing AI!