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AI Agent Development

Getting Started with AI Agents Right Away – From Essential Basics to Practical Knowledge That Everyone Needs to Use Immediately!

This is a course that beginners can follow along with in a fun and easy way. Beyond simple chatbots, AI Agents that automate industry-specific business workflows. This course quickly covers the basic structure and core technologies of AI Agents (LangChain, LangGraph, RAG) in 1.5 hours, and is an introductory course where you build practical skills by directly creating mini agents that work with actual code. After completing the course, you'll understand the necessity of industry-specific data preprocessing and scalable design, and be prepared for advanced concepts covered in deeper courses.

(4.5) 2 reviews

20 learners

Level Beginner

Course period Unlimited

  • kyoungsh7152
Python
Python
RAG
RAG
AI Agent
AI Agent
LangGraph
LangGraph
Model Context Protocol
Model Context Protocol
Python
Python
RAG
RAG
AI Agent
AI Agent
LangGraph
LangGraph
Model Context Protocol
Model Context Protocol

What you will gain after the course

  • Implementing Agents Using Python

  • Considerations for Practical Implementation of AI Agents

  • Overall knowledge about RAG agents

AI Agent Era: Master the Core Operating Principles of LLM and RAG in 90 Minutes

⭐ Course Planning Background: Why Should You Learn LLM and RAG Now?

  • Technology that safely utilizes our company's sensitive internal knowledge (Internal Data) and dramatically improves model response accuracy

  • Creating 'practical value' by combining with corporate knowledge, the core driving force of AI agents, RAG (Retrieval-Augmented Generation)

I recommend this for people like this

AI/ML Engineers and Developers

"Beyond code, I want to design an AI system that integrates knowledge!" Practitioners who want to go beyond the level of LLM API calls and directly build production-grade AI agents that operate on top of a company's vast internal knowledge

IT Planner and Product Owner

"I want to make decisions like an expert on LLM adoption ROI and technology strategy!" Decision-makers for whom successful business adoption strategies, costs, and risk management of LLM projects are more important than technical depth

Data Scientist and Researcher

"Finding proven optimization techniques to maximize LLM reliability to the extreme!" An expert who already understands the operating principles of LLMs and seeks to maximize accuracy and data utilization capabilities to meet enterprise requirements

After taking the course

  • Defining the Role of AI Agents: Clearly understand what roles AI agents perform in complex LLM-based systems and the mechanisms of how they operate in conjunction with external tools.

  • Anatomy of RAG Architecture: We break down the core components of RAG systems (Loader, Splitter, Embedding, Vector DB, Retriever, Generator) and identify the optimization points for each stage.


  • Establishing Decision Criteria (Fine-tuning vs. RAG): When improving LLM performance, we establish practical decision criteria for choosing between Fine-tuning and RAG from the perspectives of cost, data security, and recency.

Features of this course

We introduce the key features and differentiators.

Gemini_Generated_Image_1gpfv21gpfv21gpf

Solving LLM's Fatal Flaws: 100% Reliability Boost Through RAG

Through this course, students will learn how to build AI systems with "100% reliability" based on "verified evidence (Grounded Knowledge)", rather than being simple LLM callers.

Gemini_Generated_Image_bqwoc0bqwoc0bqwo

90-Minute Complete Roadmap: From Beginner to Production-Grade AI Agent Design

Through the course, you will ultimately gain the capability to design a complete deliverable called "Production Ready AI Agent".

The person who created this lecture

  • AI theory and field experience combined in an unparalleled background
    🎓 Academia and Educational Innovation
    - Starting with Electrical/Electronic Engineering at Seoul National University and completing up to the doctoral program in Computer Engineering, building deep academic foundation from AI system fundamentals to cutting-edge technologies
    - Adjunct Professor in Computer Engineering at Sejong University
    - Founded AI-based math learning service
    - Operating AI Tutor-based English learning service

    📈 Core of Business Success Story
    - Key member of 2 KOSDAQ-listed companies
    - Head of Development Division at AI BIO company

    🌍 Global Leadership
    - CCaaS(Contact Center as a Service) Tech Lead based in Silicon Valley, USA
    - Delivering vivid knowledge from experiencing and applying the latest trends in LangChain, LangGraph, RAG one step ahead of Korea

  • ✨ Why You Should Learn from This Instructor
    - Successfully led large-scale AI projects across various industries including healthcare, education, and global tech sectors


💬 Frequently Asked Questions from Students (A.K.A. Time to Resolve Your 'Real' Curiosities!)

Q1. Um... I've done a little coding, but LLM and RAG are quite unfamiliar to me. I'm not a complete beginner, but could a novice also take this course? 🥹

Yes! Absolutely! Actually, think of this course as a 'cheat key' designed specifically for people like you! 🚀 Since LLMs are so hot these days, you probably thought "I should try this too!" and called the API a few times, but when you tried to input your company's data, you got hallucinations and felt frustrated, right? This course will solve that vague uncertainty. Rather than complex theories, we'll focus on "So how exactly should I use this?" and help you understand all the core principles of LLM and RAG within 90 minutes. As long as you have basic coding skills, you'll be fine! 💪

Q2. I keep using just the GPT API all the time, but everyone's going crazy about how good RAG is... If I learn it now, what will dramatically change? Will there be a dramatic transformation? 🤨

A2. Oh, dramatic? Yes, it's way more than that! 🤩 If you're currently just using the GPT API, you've probably noticed that while LLMs do give plausible-sounding answers, there's always that nagging feeling of "Is this actually correct?" RAG is like giving your LLM 'solid reference materials' instead of 'brain speculation'. In other words, it makes the LLM reference your company's latest manuals, confidential reports, and customer service records accurately! safely! when providing answers. Hallucinations decrease, answer reliability skyrockets! It's not just adding a feature - think of it as a level up in LLM utilization! 👍

Q3. Our team is also discussing LLM adoption, but we keep fighting with the development team over "fine-tuning vs RAG"... 😂 If I take this course, can I end this tiresome debate?

A3. 😆😆😆😆😆 No more tedious debates - we can finally put an end to them! 😇 By taking this course, you'll be able to establish clear criteria for when to use fine-tuning and when to use RAG. You'll get answers to the questions that PMs and planners are most curious about, such as "How much will it cost?", "What about data security?", and "How will we reflect the latest information?" Instead of frustrating tug-of-war with the development team, you'll be able to make efficient decisions based on clear evidence. I'll help you arm yourself with the logic to convince your team! 🤝

Pre-enrollment Reference Information

Practice Environment

  • Operating System and Version (OS): Windows 10 or higher, macOS 12 or higher, Ubuntu 22.04 LTS or higher

  • Tools Used: Python

  • Development Environment: IDEs such as Visual Studio Code, PyCharm, etc. can be used

  • PC Specifications: CPU i5 or higher, Memory 16GB or higher, Disk 512GB, Integrated graphics card, etc.

Learning Materials

  • Learning materials format provided (PDF, GitHub links, etc.)

  • Features and precautions regarding volume, capacity, and other learning materials, etc.

Prerequisites and Important Notes

  • It would be great if you have some simple Python coding experience


  • Questions/answers and future updates will be conducted as needed.

  • All copyrights for lecture-related content, including lectures and learning materials, belong to the author.

  • Without prior written consent from the copyright holder, any unauthorized reproduction, distribution, transmission, creation of derivative works, and commercial use of this material is strictly prohibited.

Recommended for
these people

Who is this course right for?

  • Beginner in AI agents

  • Those who took the RAG agent development course but need a simple summary

Need to know before starting?

  • python

Hello
This is

Hello, I am AI Monster, someone who is deeply fascinated by IT and AI technology!

I majored in Computer Science at Seoul National University and have served as a core member at major corporations and global tech companies. While I have many notable career highlights (KOSDAQ listing, Head of Engineering, US Tech Lead, etc.), in truth, I am just another developer and researcher who, like you, gets excited by new technology yet sometimes feels overwhelmed by it.

The reason I am meeting you here as an instructor is because I want to drastically accelerate your growth by sharing the "knowledge I've gained through trial and error" and the "practical know-how that actually works" in the field.

Technology is changing rapidly every day. The content I teach today might be replaced by a new framework or model tomorrow. That is why I consider myself not as someone 'teaching you', but as a 'colleague learning and contemplating together at the very forefront'.

Our course is not about 'one-way knowledge transfer', but is more like a 'lab where we solve problems and evolve together'.

With AI Monster:

  • Reduce unnecessary trial and error by following the most practical and reliable roadmap.

  • Learn how to simplify complex technologies and apply them to your work immediately.

  • Let's grow together while leading IT trends through new lectures that will continue to be uploaded in the future.

I promise to be your reliable 'AI Monster Trainer' by remaining humble yet passionate, and constantly exploring new knowledge.

Let's conquer the AI era together! Thank you!

Curriculum

All

7 lectures ∙ (1hr 11min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

2 reviews

4.5

2 reviews

  • vmfmgl1221님의 프로필 이미지
    vmfmgl1221

    Reviews 14

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    Average Rating 4.6

    4

    100% enrolled

    • kangilpark8190님의 프로필 이미지
      kangilpark8190

      Reviews 1

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      Average Rating 5.0

      5

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      • kyoungsh7152
        Instructor

        I'm glad it was helpful!

    $9.90

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