本課程《LLM 大師課：精通 ChatGPT、Gemini、Claude、Llama 3、OpenAI 與 API 實戰》由 Arnold Oberleiter 講授，系統深入講解大語言模型（LLM）的核心原理、架構演進與實戰應用，覆蓋 GPT-4o、RAG、提示詞工程、模型微調、多模態理解、開源與閉源模型對比等關鍵內容。無論你是開發者、AI 從業者，還是希望掌握 AI 智能體構建的技術愛好者，本課程都將帶你全面理解並掌握 LLM 生態的全貌。
你將實操調用 OpenAI、Gemini、Claude 等主流 API，藉助 LangChain、Flowise、CrewAI 等工具開發 AI 代理，掌握向量資料庫、提示優化、Zapier 集成、本地部署開源模型（如 Llama 3、Mixtral）等能力，構建智能應用並保障安全性。課程無需前置知識，適合所有希望系統掌握生成式 AI 核心技術與實戰技能的學習者。
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教程名稱：LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs
下載連結：https://www.nidown.com/chatgpt-823093.html
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點擊查看詳情：https://www.kkmac.com/go/chatgpt
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英文原版介紹
Published 6/2024
Created by Arnold Oberleiter
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 155 Lectures ( 19h 22m ) | Size: 15 GB
Basics to AI-Agents: OpenAI API, Gemini API, Open-source LLMs, GPT-4o, RAG, LangChain Apps, Colab, Prompt Engineering
What you’ll learn:
Functionality of LLMs: Parameters, Weights, Inference, and Neural Networks
Understanding Neural Networks
Operation of Neural Networks with Tokens in LLMs
Transformer Architecture and Mixture of Experts
Fine-Tuning and the Creation of the Assistant Model
Reinforcement Learning (RLHF) in LLMs
LLM Scaling Laws: GPU & Data for Improvements
Capabilities and Future Developments of LLMs
Use of Tools by LLMs: Calculator, Python Libraries, and More
Multimodality and Visual Processing with LLMs
Multimodality in Language as in the Movie 『Her』
Systems Thinking and Future Prospects for LLMs
Self-Improvement after AlphaGo (Self-Improvement)
Improvement Possibilities: Prompts, RAG, and Customization
Prompt Engineering: Effective Use of LLMs with Chain of Thought and Tree of Thoughts Prompting & More
Adaptation of LLMs through System Prompts and Personalization with ChatGPT Memory
Long-Term Memory with RAG and GPTs
The GPT Store: Everything You Need to Know
Using GPTs for Data Analysis, PDFs, or Tetris Programming
Embeddings and Vector Databases for RAG
Integrating Zapier Actions in GPTs
Open-Source vs. Closed-Source LLMs
API Basics
Usage of the Google Gemini API and Claude API
Microsoft Copilot and Its Use in Microsoft 365
GitHub Copilot: The Solution for Programmers
The OpenAI API: Features, Pricing Models, and Everything You Need to Know About the OpenAI API Including App Creation
Introduction to Google Colab for API Calls to OpenAI
Creation of AI Apps and Chatbots with Langchain, Flowise, Vectorshift, LangGraph, CrewAI, Autogen, Langflow & more
Creation of AI Agents for Various Tasks like Social Media Contetn with Agency Swarm and Langchain Agents
Security in LLMs: Jailbreaks and Prompt Injections & more
Comparison of the Best LLMs
Google Gemini in Standard Interface and Google Labs with NotebookLM
Claude by Anthropic: Overview
Everything About Perplexity and POE
OpenAI Playground: Features, Billing Account & Temperature of LLMs
Google Gemini API: Video Analysis and More
Open-Source LLMs: Models and Use of Llama 3, Mixtral, Command R+, and Many More
HuggingChat: Interface for Open-Source LLMs
Running Local LLMs with Ollama and Building Local Rag Chatbots
Groq: Fastest Interface with LPU
Installation of LM Studio for Using Local Open-Source like Llama3 LLMs for Maximum Security
Using Open-Source Models in LM Studio and Censored vs. Uncensored LLMs
Fine-Tuning an Open-Source Model with Huggingface
Creating Your Own Apps via APIs in Google Colab with Dall-E, Whisper, GPT-4o, Vision, and More
Microsoft Autogen for AI Agents
CrewAI for AI Agents
Flowise with LangChain Function Calling
OpenAI Assistant API with function Calling for AI-Agents in different Frameworks
Flowise with Open-Source LLM as ChatBot
Security in LLMs and Methods to Hack LLMs
Future of LLMs as Operating Systems in Robots and PCs
Requirements:
No prior knowledge required, everything will be shown step by step.
