LangChain with TypeScript - LLM & RAG Introduction

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.

We explore how to create an AI judge by combining knowledge graphs, reasoning systems, and various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology.

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

Explore how LLM applications are shifting the development paradigm. Understand why LLMs are becoming a sustainable core technology through comparisons with existing technologies, and learn about the essential skills and mindset shifts required for developers. Gain insights from expert instructors to grasp the essence and future direction of LLM application development.

This is the edited live video from the LLM Application Experience Sharing Session with knowledge sharer Kang Byung-jin :)

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

This is a tutorial-style Claude code development course that even beginners and those new to development can easily follow. Based on experience teaching offline classes for planners, designers, and non-developers, you can learn everything in a single flow—from basic examples not covered in books to intermediate development projects. Using Claude code, you will experience the step-by-step development process, starting from "Hello World" to a Lucky Draw app, a device-optimized cafe menu management web page integrated with Claude design and Excel data, and finally a SaaS web application that can be uploaded to databases and cloud services. Tutorials are provided in stages of theory, practice, and projects. Through six levels of hands-on exercises, you will master AI-collaborative development methodologies and experience the entire development cycle, including cloud deployment and operation.

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.

Design and create your own student-customized AI Tutors and AI Avatars using generative AI such as ChatGPT and Gemini along with Google Colab. From prompt engineering and data analysis to building an AI Career Exploration Platform for career and academic counseling, you will complete practical projects that can be immediately applied in the classroom.

Master the complete lifecycle of building modern Generative AI applications using Large Language Models, Retrieval-Augmented Generation, and Agentic AI systems. Learn to design enterprise-grade AI solutions from prompt engineering to deployment, combining LLMs with vector databases and external knowledge sources for production-ready applications.

Beyond a chatbot that simply generates answers, you will directly implement an autonomous AI Agent that makes its own judgments, calls tools, and performs multi-step tasks. You will learn through step-by-step practice, covering everything from OpenAI Agents SDK's Tool Calling, Handoff, Guardrail, Session, and Tracing to connecting external tools and databases using MCP, as well as LangChain and Deep Agents' Planning, Subagents, Filesystem, and Memory. The ultimate goal is to equip you with the ability to design and implement tool-integrated AI Agents that can be applied to real-world tasks.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

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

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

"How is a 1-trillion parameter model trained?" Discover the scaling strategy of Kimi K2.5, revealed directly on stage by Moonshot AI at GTC 2026, in Korean on Inflearn. 2x token efficiency · 1 million token context · 1,000 agent swarm The next step for open-source LLMs is here. * This lecture is released for free through an official collaboration between Moonshot AI, the creator of Kimi, and Inflearn.

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.

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

Learn how to utilize AI prompts applicable to actual tasks and strategies for organizing an AX (AI Transformation) team. Through a systematic workflow-based approach, you will automate repetitive tasks and complete practical business automation solutions that can be immediately applied to the field.

Learn the entire process of running the latest Gemma 4 model directly on your MacBook without the burden of paid API costs. You will master performance maximization techniques using Apple Silicon's Metal API and optimal parameter settings for different VRAM capacities, while gaining the ability to build production-level local AI infrastructure based on FastAPI.