多模型 AI 应用开发实战课：用 Qwen2.5、DeepSeek、Ollama 与 ChatGPT 构建本地化智能系统

本课程系统讲解如何使用 Qwen 2.5、DeepSeek、ChatGPT、Mistral、Gemma、LLaMA 等大语言模型，结合 Ollama 工具进行本地部署与开发实战。你将学习如何构建 AI UI 应用、运行 CLI 命令、调用 API 并进行微调训练，快速实现跨模型多平台智能应用原型。课程适合有基础命令行操作能力的开发者与 AI 爱好者，是探索本地化 LLM 部署与应用开发的实用路径。

本教程为高质量英文原版视频课程，英文基础较弱的同学可通过翻译插件辅助学习。

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教程名称：AI Development with Grok, Qwen2.5, Deepseek & ChatGPT

下载连结：https://www.nidown.com/chatgpt-423183.html

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点击查看详情：https://www.kkmac.com/go/chatgpt

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英文原版介绍

Last updated 6/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 4m | Size: 1.95 GB

Build real-world AI apps with Qwen 2.5, Deepseek, ChatGPT, Mistral, Gemma, LLama, Python & Ollama. Master fine tuning.

What you’ll learn

Understand what are large language models (LLMS) and how it works
Build AI-powered applications using Deepseek, Qwen2.5 and Ollama
Setting Up and Running Qwen 2.5 and DeepSeek Locally Using Ollama
Create UI Application that Interacts with Large Language Model such as Qwen and Deepseek
Use Ollama CLI with Qwen2.5 and Deepseek
Basic command-line proficiency (executing scripts, installing packages)
Master fine tuning with Qwen2.5
Learn AI Development With Grok
Learn AI Development with ChatGPT

Requirements

A computer with macOS, Windows, or Linux
Internet connection
Optional: Python Proficiency for Enhancing Real-World Cases Presented in the Course with Greater Complexity
Essential command-line skills (running scripts, managing packages)