[VLM101] Building a Multimodal Chatbot with Fine-tuning (feat.MCP / RunPod)

Name: [VLM101] Building a Multimodal Chatbot with Fine-tuning (feat.MCP / RunPod)
Price: 77000 KRW
Rating: 4.6 (27 reviews)

This is an introductory course for understanding the concept and application methods of Vision-Language Models (VLM), and practicing running the LLaVA model in an Ollama-based environment while integrating it with MCP (Model Context Protocol). This course covers the principles of multimodal models, quantization, service development, and integrated demo development, providing a balanced mix of theory and hands-on practice.

(4.6) 27 reviews

173 learners

Level Basic

Course period Unlimited

dreamingbumblebee

Vision Transformer

transformer

Llama

Model Context Protocol

Vision Transformer

transformer

Llama

Model Context Protocol

Reviews from Early Learners

4.6

5.0

양근영

30% enrolled

This is a great training session.

5.0

홍기록

30% enrolled

It was great to gain foundational knowledge about Vision Language Models. Thank you.

5.0

내일은 한걸음 더 나아갈거야

52% enrolled

Thank you for the great lecture.

What you will gain after the course

Understanding what MCP is
Hands-on VLM Tuning and Building a PoC Demo

We use AI services like ChatGPT, Gemini, and Claude every day, but have you ever wondered how they 'understand' images? The core technology is the Vision-Language Model (VLM).

In this course, you'll fine-tune the latest VLM models like LLaVA and Qwen2.5v, run them locally with Ollama, and build your own multimodal chatbot using MCP (Model Context Protocol). We'll also cover practical skills you can apply directly to real-world work, such as CLIP Vision Encoder, Quantization, and MCP Server setup. Beyond simple API calls, you'll experience the complete workflow from understanding how VLMs work to integrating with MCP.

✅Hands-on Multimodal AI Experience - Build It Yourself, Not Just API Calls
Go beyond simply using models - this is a practice-focused curriculum where you directly tune, connect, and complete them.

✅Experience the evolution of VLM technology step by step
Systematically experience the development process of multimodal models from CLIP → LLaVA → LLaVA 1.5 → OneVision.

✅Incorporating the Latest Multimodal Technology
Covers the most recent multimodal AI trends including LLaVA OneVision, MCP, and more.

✅ GPU hands-on practice designed to complete with $10
Based on RunPod environment, all hands-on exercises can be completed at an affordable cost.

✅Build your own portfolio through this course
Upon completion, you'll have your own multimodal chatbot as a tangible result.

💡 A course for students who need this

😤 "I'm frustrated with just using APIs"

Those who built a service with ChatGPT API but feel frustrated due to cost burden and many limitations
Those curious about the inner workings of black-box AI models and want to get hands-on experience

💸 "AI service operating costs are too expensive"

Startup developers considering building their own model due to the burden of OpenAI Vision API costs
Those planning a service that requires processing large volumes of images

🚀 "I want to become a multimodal AI expert"

Those who want to advance their career as an AI developer but have only worked with text-based LLMs
Job seekers who want to add differentiated projects to their portfolio

🤔 "I'm not sure exactly what VLM is"

Those who want to keep up with AI trends but don't fully understand what multimodal or VLM is
Those curious about the principles of AI that processes images and text simultaneously

After taking this course

You can fully understand the operating principles of CLIP and LLaVA series. Multimodal AI will no longer be a black box.. AI đa phương thức sẽ không còn là hộp đen nữa.
You can fine-tune and deploy VLM in a practical environment using Ollama and RunPod.
With Quantization techniques, you can make huge models lightweight so they can run even on personal PCs.
You can build a workflow that integrates multiple AI tools using MCP (Model Context Protocol)..
You'll be able to create your own multimodal chatbot from start to finish. từ đầu đến cuối.

💡 Concrete Changes You'll Gain After Taking the Course

🎯 Immediately Applicable Practical Skills

After completing the course, you'll be able to independently work on the following real-world projects:

Your Own VLM Service: Image analysis chatbot specialized for specific domains (medical, education, shopping, etc.)
Local AI Workflow: An automated system where multiple AI tools collaborate using MCP
Cost-Effective AI Services: Services that reduce API dependency and operate with proprietary models

📈 Portfolio for Career Development

GitHub Repository: A well-organized repository with complete practice code and trained models
Technical blog material: Can write technical posts documenting the VLM fine-tuning process and results
Interview Experience: A differentiated interview story with "hands-on experience fine-tuning VLM"

🧠 Deep Understanding and Application Skills

Beyond simple usage:

Fully understand the internal workings of VLM to quickly learn new models as well
Apply model optimization techniques such as Quantization, GGUF conversion to other projects as well
The ability to design AI workflows utilizing the MCP ecosystem

Practice Environment

The course is explained based on MacOS. If you're using a Windows machine, you should be able to follow along as long as Docker is installed.
The course uses Cursor. I believe you can follow along without any issues using the VSCode version as well.
Cloud Environment
- RunPod: GPU instance rental service, using H100 or A100
- Estimated Cost: $10 for the entire hands-on practice
- Advantages: Can practice immediately without complex environment setup
- ⚠ Important Notice
  - RunPod account creation and payment card registration required

Recommended for
these people

Who is this course right for?

For those new to Multimodal and VLM
People who want to create an MCP-based demo

Need to know before starting?

LLM Fundamentals

Hello
This is dreamingbumblebee

400

Learners

Reviews

Answers

4.5

Rating

Courses

📱contact: dreamingbumblebee@gmail.com

Curriculum

All

23 lectures ∙ (2hr 52min)

Course Materials:

Lecture resources

Section 1. Orientation

1 lectures ∙ (2min)

1. Orientation - Course Introduction
02:11

Section 2. Understanding Vision Language Model (VLM)

6 lectures ∙ (54min)

2. What is VLM & Multimodal LLM(MLLM)?
01:27
3. CLIP Vision Encoder
07:46
4. LLaVA
13:21
5. LLaVA 1.5
08:42
6. LLaVA NeXT (1.6)
07:28
7. LLaVA OneVision
15:59

Section 3. VLM Finetuning & Quantization Lab

8 lectures ∙ (1hr 10min)

8. [Lab] Runpod Introduction
02:55
9. [Lab] Ollama Intro
03:53
10. [Hands-on] Uploading My Own Model to Ollama (+Demo Screen)
04:13
11. [Hands-on] RunPod Setup (feat. cursor/vscode)
11:13
12. [Hands-on] VLM SFT Hands On - Jupyter Notebook
22:08
13. [Lab] VLM SFT Hands On - HF Accelerate
06:07
14. [Hands-on] GGUF Conversion and Uploading Your Own Model to HuggingFace Hub
08:42
15. [Lab] Applying Quantization to VLM (feat. llama.cpp & gguf & ollama)
10:55

Section 4. Understanding Model Context Protocol (MCP) and PoC Demo Development

5 lectures ∙ (17min)

Section 5. Chat Demo Implementation Practice (Hands On)

3 lectures ∙ (28min)

Published: 07/08/2025

Last updated: 07/08/2025

Reviews

All

27 reviews

4.6

27 reviews

gy0930yang5791
Reviews 1
∙
Average Rating 5.0
03/11/2026
5
30% enrolled
This is a great training session.
wisebazo
Reviews 3
∙
Average Rating 5.0
03/04/2026
5
100% enrolled
haychoi2272
Reviews 1
∙
Average Rating 5.0
03/12/2026
5
65% enrolled
kirok927369
Reviews 3
∙
Average Rating 4.7
03/11/2026
5
30% enrolled
It was great to gain foundational knowledge about Vision Language Models. Thank you.
kw21kim3560
Reviews 1
∙
Average Rating 5.0
03/05/2026
5
30% enrolled

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Reviews from Early Learners

4.6

What you will gain after the course

Learn the Latest Multimodal Technology, VLM
through Fine-tuning & Chatbot ImplementationFine-tuning & Xây dựng Chatbot

5 key points you'll experience
in this course ✨

We recommend this course for

💡 A course for students who need this

After taking this course

💡 Concrete Changes You'll Gain After Taking the Course

Here's what you'll learn.

Who Created This Course

Notes Before Taking the Course

Practice Environment

Learning Materials

Prerequisites and Important Notes

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