diff --git "a/docs/\346\234\272\345\231\250\345\255\246\344\271\240\347\263\273\347\273\237/CSE234.en.md" "b/docs/\346\234\272\345\231\250\345\255\246\344\271\240\347\263\273\347\273\237/CSE234.en.md"
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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
+
+<!-- 
+        Introduce the course in a paragraph or two, including but not limited to:
+        (1) The technical knowledge covered in lectures
+        (2) Its differences and features compared to similar courses
+        (3) Your personal experiences and feelings after studying this course
+        (4) Caveats about studying this course on your own (pitfalls, difficulty warnings, etc.)
+        (5) ... ...
+-->
+
+
+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/
diff --git "a/docs/\346\234\272\345\231\250\345\255\246\344\271\240\347\263\273\347\273\237/CSE234.md" "b/docs/\346\234\272\345\231\250\345\255\246\344\271\240\347\263\273\347\273\237/CSE234.md"
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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
+
+<!-- 用一两段话介绍这门课程，内容包括但不限于：
+    （1）课程覆盖的知识点范围
+    （2）与同类课程相比它的优势与特点
+    （3）学习这门课程的体验与感受
+    （4）自学这门课的注意点（踩过的坑、难度预警等等）
+    （5）... ...
+-->
+
+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/
+