Computer Vision & Large Language Model Projects on Raspberry Pi 5 (Chinese)

課程簡介

對在 Raspberry Pi 上部署大型語言模型（LLM）感到好奇，卻沒有實體裝置？本課程提供雲端遠端實作環境，讓你無需硬體也能完整操作。每個專題皆配有模擬的 Raspberry Pi 5 環境，實作學習更輕鬆。

課程從 Raspberry Pi 的連線與基本終端指令教學開始，帶你認識 LLM 與輕量級語言模型（SLM）之間的差異，並透過 8 個真實應用專題，涵蓋聊天機器人、語音轉錄、圖像文字擷取與多模態 AI 互動等，全面學習在低功耗邊緣裝置上部署 AI 技術。

課程特色

• 雲端實作環境，無需實體硬體設備

• 聚焦輕量語言模型與 ARM 邊緣裝置的應用

• 包含八個完整實作專題，逐步引導學員完成 AI 應用

• 支援 Windows、macOS 與 Linux 系統

• 理論與實務並重，先理解再動手實現模型部署

課程大綱

第一部分：環境建置與遠端連線

• Raspberry Pi Connect 操作教學

• Linux 基本終端機指令操作

• Windows / Mac 環境的 SSH 與 SCP 遠端連線設定

第二部分：LLM 與 SLM 基礎概念

• 主流 LLM 模型介紹（LLaMA、Gemini、Mixtral 等）

• 輕量模型（SLM）在 ARM 架構中的角色與優勢

• 模型效能、限制與實務應用場景探討

第三部分：八大應用實作專題

1. llama.cpp 聊天機器人：從建置到 Python API 整合

2. Ollama Chatbot：圖形化界面、REST API 與訊息整合

3. LangChain + Ollama：打造支援 RAG 的聊天機器人應用

4. Whisper 語音轉文字：多語言語音轉錄與 Pi 裝置最佳化

5. Ollama OCR：圖像文字辨識與文字擷取應用實作

6. LLaVA 多模態助理：結合語言與圖像的 AI 助理

7. LLM 數學應用：進行數學與邏輯推理任務模型實作

8. RAG Chatbot：從模型量化到前端部署的完整流程建置

適合對象

• 希望學習 LLM 專案實作但沒有實體裝置的學習者

• 有興趣探索輕量模型與邊緣 AI 應用的開發者

• 著重實作導向、結合 AI 與物聯網應用的教育工作者與學生

Course Overview

Curious about deploying LLMs on Raspberry Pi but don’t have the device? This course solves that problem with a Cloud-based Hands-on Lab—giving you full access to a simulated Raspberry Pi 5 environment for every project, no physical hardware needed.

You’ll start from the basics of Pi Connect and terminal commands, learn the differences between LLMs and lightweight SLMs, and progress through 8 real-world application labs including chatbot building, voice transcription, image text extraction, and multimodal interaction—all tailored for low-power edge devices.

What Makes This Course Special

☁️ Cloud Hands-on Lab: Practice remotely in a full Pi simulation—no hardware required

💡 SLM & Edge Focus: Learn small model deployment and ARM optimization

🧰 8 Complete Labs: Build real AI applications step-by-step

🖥️ Cross-platform Friendly: Windows, macOS, and Linux supported

📘 Theory Meets Practice: Understand the models before you build with them

Course Outline

Part 1: Environment Setup & Remote Access

• Raspberry Pi Connect walkthrough

• Basic Linux terminal commands

• Remote access setup (SSH/SCP) for Windows / Mac

Part 2: LLM & SLM Fundamentals

• Overview of popular LLMs (LLaMA, Gemini, Mixtral, etc.)

• SLMs and their role in ARM environments

• Limitations, potential, and use cases of small models

Part 3: Eight Hands-on Project Labs

1. llama.cpp Chatbot – From setup to Python API deployment

2. Ollama Chatbot – GUI modules, REST API, messaging integrations

3. LangChain + Ollama – Build RAG-powered interactive chatbots

4. Whisper Speech-to-Text – Multilingual transcription + RPi 5 optimization

5. Ollama OCR – Extracting text from images and OCR principles

6. LLaVA Assistant – Multimodal AI running on Raspberry Pi 5

7. LLM for Math – Model comparison and math/logical reasoning tasks

8. RAG Chatbot – End-to-end deployment from model quantization to frontend

Who Should Enroll

• Learners who want to build and deploy LLM projects without hardware

• Developers exploring lightweight models for edge environments

• Educators and students focused on practical AI and IoT integration

Pricing Notice

Product prices are displayed in your local currency for your convenience. However, all payments will be processed in New Taiwan Dollars (TWD) at the final checkout based on the current exchange rate.