graphRAG - Knowledge Graph-based RAG System Implementation with Neo4J (feat. LangChain)

Implementing a Retrieval-Augmented Generation (RAG) Intelligent AI Agent with LangGraph! From theory to practice, this is a hands-on tutorial that even beginners can easily follow.

This lecture covers RAG (Retrieval-Augmented Generation) system fundamentals and implementation using LangChain. Participants will understand RAG's core principles and learn to build and evaluate systems using LangChain.

This is a basic Python course for non-major beginners. Practice materials are provided through Github.

Learn LangChain's basic concepts and usage with Python. Hands-on practice will be conducted primarily in a Google Colab (colab) environment, with materials provided via Github.

Create your own AI chatbot using Python's basic syntax and libraries. Learn through a step-by-step process of completing 5 projects, including PDF document-based RAG, and deploy them as web services.

This course is designed for beginners and consists of easy explanations and various hands-on projects. It covers data collection using web crawling and LangChain tools, and summarization, extraction, sentiment analysis, and recommendation systems using LLM.

This lecture covers RAG (Retrieval-Augmented Generation) system fundamentals and implementation using LangChain. Participants will understand RAG's core principles and learn to build and evaluate systems using LangChain.

Implementing a Retrieval-Augmented Generation (RAG) Intelligent AI Agent with LangGraph! From theory to practice, this is a hands-on tutorial that even beginners can easily follow.

This course is designed to provide step-by-step learning from the basic concepts of database systems to the utilization of Relational Database Management Systems (RDBMS) and SQL. Learners will understand the principles of databases and be able to create systematic data structures through data modeling and design methods. Additionally, they will experience actual data processing by practicing data manipulation and management techniques using SQL. Through this course, students can go beyond simple theoretical learning to build a foundation that can be utilized for both practical work and certification exam preparation by acquiring efficient data management and application skills.

AI Era-Proof Silicon Valley Internship & 30 Big Tech System Design & Open Source Practical Contribution Complete Course Mission Submission All students can apply for a US Palo Alto local AI startup internship, with document screening exemption and interview opportunities provided, and this is a course where you design and scale 30 practical system designs using big tech cases like Netflix, Tesla, Meta, Tinder, etc. At the end, you design your own service from architecture → DB → scaling, contribute to an actually operating open source AI coding agent project (achieving 1.8k downloads per week), complete your portfolio, and finalize your resume.

A beginner's guide to SQL coding! We'll teach you the secrets of writing, interpreting, and validating SQL.

Through this lecture, you can learn about understanding SQL and databases, SQL syntax, database design for practical application, database utilization through programming, and even data analysis application cases.

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

I have summarized the essential SQL SELECT statements and basic usage of Google Sheets that I learned while working as an analyst at a service company.

Learn database design systematically through three stages: conceptual, logical, and physical, and strengthen your capabilities with a practical shopping mall project. Acquire real-world expertise through modern design techniques and the latest trends.

🧩 Rather than focusing on complex formulas or theory-centric explanations, the goal is to learn the core concepts of recommendation systems by directly implementing programs. 🛠️ Through a total of 12 diverse and practical examples, we have progressively designed recommendation systems that can be utilized in real-world environments, including content-based recommendation, collaborative filtering, and deep learning recommendation.

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

Not only developers, but also planners and data analysts learn databases step-by-step, starting from SQL basics.

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.

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

What does the 'Business Information Visualization Competency Certificate' course teach? This certificate course focuses on developing the ability to analyze data well, visualize it in an easy-to-understand way, and clearly and effectively convey necessary information when making important decisions in a company or organization. In simple terms, it's a course that teaches not just how to view data, but how to find the hidden meaning within it, and how to express it using images, tables, and graphs so that it can be clearly explained to others. Through this course, you will: Develop the ability to think strategically through data, cultivate practical skills immediately applicable to real work, and enhance your expertise and competitiveness. Through this lecture, develop the ability to connect management and data, and take another step forward as an expert in understanding and explaining data.

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.

By implementing various practical data analysis cases using SQL, you can simultaneously improve your data analysis and SQL utilization skills.

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

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.