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AI Agent Development

Made in RAG(Local LLM QA System) With Docker + ollama + R2R

In just 2 hours of hands-on practice, we build a local LLM with RAG-based QA system using the Docker + ollama + R2R framework. (Internal/in-house QA systems, personal portfolios, AI-powered work capabilities, and even commercial services are possible.)

(5.0) 3 reviews

23 learners

  • kojeomstudio
실습 중심
Docker
AI
wsl
LLM

Reviews from Early Learners

What you will gain after the course

  • You will learn how to operate an LLM locally.

  • Implementing the fabled AI Q&A system locally.

  • Build an AI Q&A system based on specific domain knowledge.

  • You will learn how to build a Docker-based AI system.

  • You will learn how to utilize AI open source projects.

  • An in-house/internal local (or generative AI API) LLM-based RAG system will be implemented.

  • One step closer to realizing AI systems that felt distant.

  • I learn about 'ollama', the ultimate LLM open framework.

I want to create an LLM-based QA system... How should I build it?

The development of AI technology that feels endlessly difficult!

1) Welcome to the world of AI with a local LLM QA system using Docker, ollama, and R2R framework!

2) From AI infrastructure technology to practical open-source project applications with quick and easy steps!

3) You can build an On-premise solution without security concerns for internal/in-house use!

The Features of This Course

📌 After completing the course, build an in-house Local and commercial LLM-based RAG system that you can use immediately in practice!

📌 You can develop a sense for AI-related open source projects.

📌 You'll gain opportunities to develop and utilize AI technology that may have seemed distant before.

📌 You will experience infrastructure and operating system concepts such as Docker and WSL that are necessary for artificial intelligence (AI) technology infrastructure.

We recommend this for:

I want to try utilizing AI and artificial intelligence technology within our company.

You're a programmer who wants to try AI utilization that you hear about everywhere, but you don't know where to start!

I want to add AI experience to my programmer portfolio~
Programmers and job seekers who are secretly worried because they've never used AI-related technologies even once in the AI era!

Curious about AI-related open source projects!
Developers wondering how to use related open source projects in the AI era!

After taking the course

  • You'll find yourself taking a step forward in utilizing AI technology before you know it.

  • You will become known in the company as a developer who built an AI system.

  • You'll find yourself surprised, thinking "AI development was this close to me all along!?"

  • You will gain a deeper understanding of the concepts of artificial intelligence and AI.

  • You will learn the concepts and usage methods necessary for infrastructure such as WSL and Docker.

  • You will learn about AI Q&A systems through LLM-based RAG systems.

You will learn the following content.

Convenient embedding work through R2R dashboard

It conveniently handles domain knowledge embedding required for QA systems.

Build an LLM-based QA system that feels so distant!

Experience an LLM QA system built on ollama, docker, and wsl!

The person who created this course

Instructor Introduction

Pre-enrollment Notes

Practice Environment

  • The lecture is conducted based on Windows 10.

  • You will be using a Linux kernel-based virtual machine provided by Windows. (WSL)

  • You will be using it after installing the Docker system on WSL.


Based on the course content, it would be good to proceed with the included version (3.6.0) for R2R.

However, assuming that the R2R framework continues to improve, proceeding with the latest version shouldn't cause major issues. (You should consider that some commands or settings may change.)

For version 3.6.0, please refer to the Release Tags in the official R2R GitHub repository or check the link separately archived by the author.

github

docker hub: docker pull kojeomstudio/r2r:3.6.0

  • You can also pull version 3.6.0 directly. (image created by the author)


p.s. For R2R-dashboard, since there are few changes, you can use the latest version.

Learning Materials

Recommended for
these people

Who is this course right for?

  • Programmer wanting to try implementing an AI system

  • Aspiring programmer looking to build an AI system portfolio

  • Programmer who wants to build an in-house, specific domain-based AI Q&A system

  • Person looking to run LLM locally.

  • Programmer wanting to ride the AI wave

  • Developers aspiring to build Docker-based AI systems

  • AI open-source project novice

  • Programmer eager to apply AI open-source projects in practice

Need to know before starting?

  • Docker

  • Basic Concepts of LLM

  • Desire and will to enhance AI proficiency

  • AI system infra build interest

  • Interest in open source projects

Hello
This is

1,071

Learners

35

Reviews

1

Answers

4.9

Rating

5

Courses

 

 

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강사 소개

Curriculum

All

7 lectures ∙ (1hr 47min)

Published: 
Last updated: 

Reviews

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3 reviews

5.0

3 reviews

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    ssyi4412

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    5

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      sund

      Reviews 5

      Average Rating 4.0

      5

      43% enrolled

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        kaciaryu9603

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        Average Rating 5.0

        5

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