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# CSE234: Data Systems for Machine Learning
## Descriptions
- Offered by: UCSD
- Prerequisites: Linear Algebra, Deep Learning, Operating Systems
- Programming Languages: Python, Triton
- Difficulty: 🌟🌟🌟
- Class Hour: 80 hours
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This course is focused on designing a wholistic LLM System class as an introduction to design efficient systems for LLM.
The class into three parts, covering the following topics.
1. Basics: deep learning, autodiff, CUDA programming, ML hardware
2. ML systems and optimizations: Dataflow graph systems, ML compilation, memory and graph optimization, ML parallelism, auto-parallelization
3. LLM systems: LLM training, data curation, inference and serving, attention optimization, scaling law, RAG, LLM agents
## Course Resources
- Course Website: https://hao-ai-lab.github.io/cse234-w25/
- Recordings: https://hao-ai-lab.github.io/cse234-w25/
- Textbooks: https://hao-ai-lab.github.io/cse234-w25/resources/
- Assignments: https://hao-ai-lab.github.io/cse234-w25/assignments/

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# CSE234: Data Systems for Machine Learning
## 课程简介
- 所属大学UCSD
- 先修要求:线性代数,深度学习,操作系统
- 编程语言Python, Triton
- 课程难度:🌟🌟🌟
- 预计学时80小时
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3学习这门课程的体验与感受
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本课程专注于设计一个全面的大语言模型(LLM)系统课程作为设计高效LLM系统的入门介绍。
课程分为三个部分,涵盖以下主题:
1. 基础知识深度学习、自动微分、CUDA编程、机器学习硬件
2. 机器学习系统与优化:数据流图系统、机器学习编译、内存与图优化、机器学习并行化、自动并行化
3. 大语言模型系统LLM训练、数据整理、推理与服务、注意力机制优化、缩放定律、检索增强生成(RAG)、Agent
## 课程资源
- 课程网站https://hao-ai-lab.github.io/cse234-w25/
- 课程视频https://hao-ai-lab.github.io/cse234-w25/
- 课程教材https://hao-ai-lab.github.io/cse234-w25/resources/
- 课程作业https://hao-ai-lab.github.io/cse234-w25/assignments/