LLM Application In Production

The ultimate full-stack course that teaches even beginners about web, server, mobile apps, and machine learning!! If you're not sure where to start with development, I highly recommend this course. It's all done with just Javascript!

Regardless of the field! This is a lecture that covers the core fundamentals that developers must know in practice in an easy + code-oriented way. I highly recommend this lecture to all junior developers and job seekers who want to grow.

I share basic background knowledge and development experience for LLM Application development.

This course is a membership subscription concept, so once you purchase it, you can continue to take additional classes😃

RAG. Learn from Silicon Valley GenAI Hackathon Winner. Packed with real-world know-how.

A Complete Guide to Building an AI Chatbot System with Langchain and RAG! Provides a systematic learning process for generative AI development 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.

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.

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

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

This is a practice-oriented course for experienced developers with a computer science background transitioning to the latest AI technology stack. From the design to the implementation of LLM-based applications, you will establish AI solution adoption strategies by leveraging existing software engineering knowledge. Rebuild your career by integrating traditional development experience with modern AI technology.

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.

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

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!

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

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

By utilizing the operating principles and development tools of Microsoft 365 Copilot agents, you can systematically learn how to design and expand agents that operate in the way you desire. Chapter 1 organizes the essential concepts and principles to know before creating an agent, Chapter 2 explores agent types and tools suitable for various scenarios, and Chapter 3 allows you to directly implement your own agent using Agent Builder, SharePoint Agent, and Copilot Studio. From basics to hands-on practice, this single course will enable you to connect the potential of Copilot agents to practical applications!

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.

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