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[FEATURE] English version support using mkdocs-static-i18n (PKUFlyingPig#224)
* feat: i18n support * add nav translation * add English template * fix translations * fix en site_name
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docs/index.en.md

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# Self Learning Computer Science Roadmap
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I'm an undergraduate student majored in Computer Science in Peking University. Tired of the boring courses, I began self-learning totally after my fresh year. This repository contains all the resources I used to self-learning. The links below will take you either to another repository which contains my solution for homework and course projects or to the course website where you can get full guidance.
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If you feel quite painful to take the courses at unversity. Trust me, there is high possibility that it's not your duty. Computer Science is so interesting and everyone should enjoy it if you have a good teacher to teach you a good course.
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All the courses in this repository are developed in MIT, UC Berkeleys, Princeton, Harvard ...... , and I guarantee you will have a completely different experience to take these courses !
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Let's self-learning together and get better together !
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If you find this repo helpful for you, your star is the best gift for me ~
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# MIT: The Missing Semester of Your CS Education
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## Descriptions
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- Offered by: MIT
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- Prerequisites: None
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- Programming lanuages: Shell
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- Difficulty: 🌟🌟
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- Class Hour: 10 hours
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Just as the course name indicated, this course will teach the missing things in the university courses. It will cover shell programming, git, vim editor, tmux, ssh, sed, awk and even how to beautify your terminal. Trust me, this will be your first step to become a hacker!
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## Resources
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- Homepage: <https://missing.csail.mit.edu/>
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- Records: <https://www.youtube.com/playlist?list=PLyzOVJj3bHQuloKGG59rS43e29ro7I57J>
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- Assignments: Some exercises behind each lecture.

mkdocs.yml

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- md_in_html
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plugins:
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- i18n:
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default_language: zh
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material_alternate: true
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languages:
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zh:
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name: 简体中文
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build: true
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en:
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name: English
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build: true
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site_name: CSDIY.wiki
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nav_translations:
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en:
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前言: Foreword
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一个仅供参考的CS学习规划: Guideline
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必学工具: Productivity Toolkit
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好书推荐: Book Recommendation
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数学基础: Fundamental Mathematics
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数学进阶: Advanced Mathematics
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编程入门: Fundamental Programming
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电子基础: Fundamental Electronics
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数据结构与算法: Data Structures and Algorithms
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软件工程: Software Engineering
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体系结构: Computer Architecture
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操作系统: Operating Systems
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并行与分布式系统: Distributed Systems
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计算机系统安全: Computer Security
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计算机网络: Computer Networking
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数据库系统: Database Systems
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编译原理: Compilers
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计算机图形学: Computer Graphics
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Web开发: Web Development
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数据科学: Data Science
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人工智能: Artificial Intelligence
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机器学习: Machine Learning
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机器学习系统: Machine Learning Systems
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深度学习: Deep Learning
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机器学习进阶: Advanced Machine Learning
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后记: Postscript
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- search:
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lang: ja
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- git-revision-date-localized

requirements.txt

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mkdocs-minify-plugin >= 0.4.0
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mkdocs-git-revision-date-localized-plugin >= 0.9.3
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jinja2==3.0.0
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mkdocs-static-i18n==0.46

template.en.md

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# Course Code: Course Name
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## Descriptions
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- Offered by:
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- Prerequisites:
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- Programming lanuages:
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- Difficulty:
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- Class Hour:
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<!-- Course Information -->
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## Resources
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- Homepage:
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- Records:
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- Textbooks & Notes & Slides:
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- Assignments:
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- ...

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