AI Agent with LangGraph version 1 From Basics to Advanced

This course on RAG (Retrieval-Augmented Generation) 👉 doesn't stop at conceptual explanations 👉 but involves building actual working structures hands-on 👉 and experiencing expansion and advancement through practice-focused learning. Starting from simple RAG examples, you'll progress step-by-step from Advanced RAG → Modular RAG → Agent-based RAG to a level that can be immediately applied in real-world work environments.

🧩 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.

This course on RAG (Retrieval-Augmented Generation) 👉 doesn't stop at conceptual explanations 👉 but involves building actual working structures hands-on 👉 and experiencing expansion and advancement through practice-focused learning. Starting from simple RAG examples, you'll progress step-by-step from Advanced RAG → Modular RAG → Agent-based RAG to a level that can be immediately applied in real-world work environments.

We explore methods for creating an AI judge by combining multiple agent frameworks such as CrewAI, LangChain, and AutoGen that enable the implementation of LLM-based multi-agent technology, along with knowledge graphs and reasoning systems.

Without a single formula or line of code, this book penetrates the essence of fundamental statistics needed for AI development and application.

Spring AI + JPA + MySQL Premium Reservation Agent Backend Development with 'Autonomous Behavior' Beyond Chatbots to Agents: The Definitive Guide to Tool Calling and Prompt Engineering

In an era of explosive data growth and crucial real-time processing, edge computing has established itself as an essential technology, no longer an option. This course is designed to systematically teach everything, from the core concepts of edge computing to deployment strategies for its application in real business environments. Through this course, students will firmly solidify the fundamental principles of edge computing and acquire practical knowledge and know-how applicable to real-world tasks and projects. Take the most certain first step towards becoming an edge computing expert, a core technology in the future IT environment!

In the midst of daily overwhelming tasks and endless repetitive work, you've probably wondered, "Isn't there a smarter and more efficient way to do this?" Haven't you felt frustrated wasting time on drafting reports, repeatedly failing to find new insights in brainstorming meetings, and struggling to keep up with competitors' pace? Right now, the most powerful tool to solve those concerns has emerged. It's Generative AI. This isn't just a trending technology. It's the most fundamental productivity revolution of our time, and those who first capture and utilize this change will become the winners of future business. This course will teach you how to immediately apply Generative AI, which will become your most capable assistant on your desk, to your actual work. Let's set aside complex theories for now. We focus on **"So what can I do with this technology starting tomorrow?"** 💡 We'll help you reclaim your time and creativity. Our core goal is your **'work automation'** and **'creativity maximization'**. 90% reduction in report writing time: Learn how to delegate the creation of reports, proposals, and email drafts that consume your precious time every week to AI. Simply input key data and direction, and AI will immediately complete professional documents for you. You can now focus on being a strategic thinker and leader, not a document writer. Ideas that outpace competitors: Need new marketing campaigns, innovative product designs, or content ideas that captivate customers? Practice using AI as a partner to instantly generate dozens of creative alternatives and predict market reactions. Data-driven smart decision making: Don't get lost in countless materials. AI quickly summarizes vast amounts of data and provides key insights, helping you make strategic judgments based on data rather than intuition. 🛠️ 'Prompts' are the new language. Utilizing Generative AI well ultimately means being good at **'prompt engineering'**. Like commanding a capable employee, the skill of giving clear and specific instructions to AI determines success or failure. In this course, we'll teach you the core formula for **"how to ask questions to get the desired results."** You'll directly write customized prompts optimized for your role - whether you're a marketer, developer, or planner - and experience how dramatically different the results can be. This knowledge will become a core future competency that won't waver no matter what new AI tools emerge. 🏆 Through this course, you'll become a 'future businessman'. Generative AI is no longer a 'choice' but a 'necessity'. If you reject this technology, your competitors will work 10 times faster every day. But if you seize this opportunity, you can be reborn as a 'future-ready talent' who maximizes productivity, leads creative innovation, and dramatically boosts business performance. Don't fear Generative AI. What matters is knowing how to utilize it well. Start your work innovation journey through this course. It will be the one decision that explodes your business potential. Register right now and experience a new way of working where you work less and achieve more.

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.

This course covers the entire process of designing and implementing generative AI services centered on LangChain 1.0 and LangGraph through step-by-step hands-on practice. Beyond simple LLM calls, you'll directly implement operational AI system architectures that include agent-based architecture, state management, memory, streaming, middleware, and Human-in-the-Loop. Through hands-on practice with document/PDF/web data-based RAG systems, SQL Agent (Chinook DB), tool-calling-based Agents, Supervisor pattern multi-agents, and state machine-based workflows using LangGraph Graph API, you'll build reusable agent pipelines that can be immediately applied in real-world scenarios. Additionally, through structured output (Pydantic-based), agent middleware (Summarization, HITL, Retry, PII protection), and token/step-by-step streaming, you'll complete generative AI applications with the stability, scalability, and controllability required in actual services. 👉 For those who want to accurately understand the internal structure and execution flow of LangChain/LangGraph 👉 For those who want to implement RAG·Agent as a real service structure, not just a "demo" 👉 This is the optimal course for those who need a realistic practical roadmap covering state-based agents, SQL·document automation, and multi-agent orchestration.

Do you still code directly these days? Now is the era where even vibe coding is too much hassle! Become an AI automation expert with n8n without coding. A practical automation workflow design guide you can apply immediately at work Action-oriented automation strategies that maximize work efficiency. Build intuitive workflows with n8n and experience workplace innovation

This course covers everything from core recommendation system algorithms to practical implementation. - Content-based filtering - Collaborative filtering and deep learning-based recommendation model implementation - Two-step recommender systems implementation - Hands-on practice using PyTorch/RecBole - Industry know-how and recommendation result visualization

You can learn the core concepts of complex Next.js in a short time. We'll teach you only the essential practical knowledge for those learning Next.js for the first time. Captain Pangyo's new Next.js course, who has been conducting framework courses for 8 years. You can learn the coding and learning methods of "Frontend Developers in the AI Era"! 😊

Excel, coding, app development—anyone can start easily with AI. Learn from Excel automation to Python basics and app creation through hands-on practice using generative AI tools like ChatGPT and Perplexity.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

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.

This course is a hands-on masterclass that completely conquers the evolution of Diffusion Models through papers and code implementation. You'll learn the core models of generative AI, including DDPM (Denoising Diffusion Probabilistic Model) and DDIM, by studying the paper principles and implementing them directly. We analyze step-by-step the background of each model's emergence, mathematical formulations, network architectures (U-Net, VAE, Transformer), training processes (Noise Schedule, Denoising Step), and the ideas that led to performance improvements. Students will directly code all models using PyTorch, gaining not just paper comprehension but 'practical skills to reproduce and apply' them in real-world scenarios. Additionally, by comparing the differences between models and their developmental flow, you'll clearly understand how they expand and evolve. This course integrates theory, code, and practice into one comprehensive journey, providing researchers, developers, and creators alike with a systematic way to master the evolution of generative models. Beyond simply 'reading' papers, start your experience of 'understanding and recreating' through direct implementation now.

We're building an AI-powered video conferencing application with real-time AI agents, meeting summary features, and post-call functionality.

An introductory AI lecture tailored for those new to AI! Key concepts, from data to generative AI, are simply explained. The goal is practical understanding, enabling you to question and explain AI, not build it.

NLP Conference <Langcon 2024> Presentation Session Video

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