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Alibaba Cloud LLM Engineer ACA Certification Study Notes

ACA Certificate

Complete LLM Knowledge System · Mind Maps + Detailed Notes

License: MIT Stars Language Update
[中文(简体)] | [English]


If you find it useful, welcome to star⭐, and you are also welcome to submit an issue for further discussion or PR proofreading.

This is a comprehensive collection of study notes for the Alibaba Cloud LLM Engineer ACA Certification Course. It includes both mind map versions and detailed notes versions for easy review, summarization, and retrieval.

If you find it helpful, welcome to star⭐, and feel free to submit issues to discuss learning insights.

Course Content

Curriculum Overview

Chapter Topic Key Content
Chapter 01 Understanding LLMs LLM fundamentals, development history, key characteristics
Chapter 02 LLM Application Scenarios Customer service, content generation, code assistants, data analysis, etc.
Chapter 03 API Usage Model API invocation, parameter optimization, error handling
Chapter 04 Prompt Engineering Prompt design principles, optimization techniques, best practices
Chapter 05 Tool Calling Plugin mechanisms, function calls, tool integration
Chapter 06 RAG Knowledge Base Document retrieval, vectorization, augmented generation
Chapter 07 Model Fine-tuning Fine-tuning methods, training strategies, vertical domain optimization
Chapter 08 Agent Applications Agent architecture, task planning, decision execution
Chapter 09 Application Security Privacy protection, security compliance, risk prevention
Chapter 10 Extended Learning Multi-modal models, MoE architecture, cloud-edge collaboration

Mind Maps

Click the chapter tabs below to jump quickly:

Chapter 01 - Understanding LLMs
Chapter 02 - LLM Application Scenarios
Chapter 03 - API Usage
Chapter 04 - Prompt Engineering
Chapter 05 - Tool Calling
Chapter 06 - RAG Knowledge Base
Chapter 07 - Model Fine-tuning
Chapter 08 - Agent
Chapter 09 - Application Security
Chapter 10 - Extended Learning

Detailed Notes

Click the chapter tabs below to view complete notes:

Chapter 01 - Understanding LLMs
Chapter 02 - LLM Application Scenarios
Chapter 03 - API Usage
Chapter 04 - Prompt Engineering
Chapter 05 - Tool Calling
Chapter 06 - RAG Knowledge Base
Chapter 07 - Model Fine-tuning
Chapter 08 - Agent
Chapter 09 - Application Security
Chapter 10 - Extended Learning

⭐ Star History

Star History Chart

📚 Reference Resources

License

Licensed under the MIT License. See LICENSE file for details.


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