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‎1-Introduction/README.md‎

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# Introduction to Data Science
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![data in action](images/data.jpg)
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>Photo by <a href="https://unsplash.com/@dawson2406?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Stephen Dawson</a> on <a href="https://unsplash.com/s/photos/data?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
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> Photo by <a href="https://unsplash.com/@dawson2406?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Stephen Dawson</a> on <a href="https://unsplash.com/s/photos/data?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
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In these lessons, you will discover how Data Science is defined and learn about ethical considerations that must be considered by a data scientist. You will also learn how data is defined and learn a bit about statistics and probability, the core academic domains of Data Science.
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### Topics
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1. [Defining Data Science](01-defining-data-science/README.md)

‎1-Introduction/translations/README.zh-cn.md‎

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# 数据科学简介
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![data in action](../images/data.jpg)
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> Photo by <a href="https://unsplash.com/@dawson2406?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Stephen Dawson</a> on <a href="https://unsplash.com/s/photos/data?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
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在这些课程中，你将了解到数据科学是如何定义的，以及数据科学家必须考虑的伦理问题。你还将学习数据是如何定义的，还有一些关于统计学和概率的知识，这是数据科学的核心学术领域。
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### 主题
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1. [数据科学的定义](../01-defining-data-science/README.md)
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2. [数据科学伦理](../02-ethics/README.md)
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3. [数据的定义](../03-defining-data/README.md)
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4. [统计与概率概论](../04-stats-and-probability/README.md)
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### 致谢
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这些课程由 [Nitya Narasimhan](https://twitter.com/nitya) 和 [Dmitry Soshnikov](https://twitter.com/shwars) 用 ❤️ 编写。

‎README.md‎

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We have chosen two pedagogical tenets while building this curriculum: ensuring that it is project-based and that it includes frequent quizzes. By the end of this series, students will have learned basic principles of data science, including ethical concepts, data preparation, different ways of working with data, data visualization, data analysis, real-world use cases of data science, and more.
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In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 12 week cycle.
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In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 10 week cycle.
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> Find our [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md) guidelines. We welcome your constructive feedback!
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>
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## Each lesson includes:
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‎translations/README.zh-cn.md‎

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在创建这个课程时，我们选择了两个教学原则：确保它是基于项目的，并且包括频繁的测验。在本系列课程结束时，学生将学会数据科学的基本原则，包括道德概念、数据准备、处理数据的不同方式、数据可视化、数据分析、数据科学的实际使用案例等等。
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此外，课前的低风险测验使学生对学习某个主题有了意向，而课后的第二次测验则确保了学生记住了内容。本课程的设计是灵活而有趣的，可以参加整个或部分课程。这些项目开始时很小，在 12 周的学习过程内会变得越来越复杂。
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此外，课前的低风险测验使学生对学习某个主题有了意向，而课后的第二次测验则确保了学生记住了内容。本课程的设计是灵活而有趣的，可以参加整个或部分课程。这些项目开始时很小，在 10 周的学习过程内会变得越来越复杂。
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> 找到我们的 [行为守则](../CODE_OF_CONDUCT.md)、[贡献](../CONTRIBUTING.md) 以及 [翻译](../TRANSLATIONS.md) 指南。我们欢迎你的建设性反馈！
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| 编号 | 主题 | 课程分类 | 学习目标 | 链接 | 作者 |
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| :-----------: | :----------------------------------------: | :--------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------: | :----: |
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| 01 | 数据科学的定义 | [简介](../1-Introduction/README.md) | 了解数据科学背后的基本概念以及它与人工智能、机器学习和大数据的关系。 | [课程](../1-Introduction/01-defining-data-science/README.md) [视频](https://youtu.be/pqqsm5reGvs) | [Dmitry](http://soshnikov.com) |
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| 02 | 数据科学伦理 | [简介](../1-Introduction/README.md) | 数据伦理的概念、挑战和框架。 | [课程](../1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) |
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| 03 | 数据的定义 | [简介](../1-Introduction/README.md) | 数据是如何分类的，以及它的常见来源。 | [课程](../1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) |
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| 04 | 统计与概率概论 | [简介](../1-Introduction/README.md) | 用概率和统计学的数学技术来理解数据。 | [课程](../1-Introduction/04-stats-and-probability/README.md) [视频](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) |
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| 01 | 数据科学的定义 | [简介](../1-Introduction/translations/README.zh-cn.md) | 了解数据科学背后的基本概念以及它与人工智能、机器学习和大数据的关系。 | [课程](../1-Introduction/01-defining-data-science/README.md) [视频](https://youtu.be/pqqsm5reGvs) | [Dmitry](http://soshnikov.com) |
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| 02 | 数据科学伦理 | [简介](../1-Introduction/translations/README.zh-cn.md) | 数据伦理的概念、挑战和框架。 | [课程](../1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) |
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| 03 | 数据的定义 | [简介](../1-Introduction/translations/README.zh-cn.md) | 数据是如何分类的，以及它的常见来源。 | [课程](../1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) |
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| 04 | 统计与概率概论 | [简介](../1-Introduction/translations/README.zh-cn.md) | 用概率和统计学的数学技术来理解数据。 | [课程](../1-Introduction/04-stats-and-probability/README.md) [视频](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) |
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| 05 | 与关系型数据打交道 | [与数据打交道](../2-Working-With-Data/README.md) | 介绍关系型数据，以及用结构化查询语言（又称 SQL）探索和分析关系型数据的基础知识（读作 “see-quell”）。 | [课程](../2-Working-With-Data/05-relational-databases/README.md) | [Christopher](https://www.twitter.com/geektrainer) |
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| 06 | 与非关系型数据打交道 | [与数据打交道](../2-Working-With-Data/README.md) | 介绍非关系型数据，其各种类型以及探索和分析文档数据库的基本知识。 | [课程](../2-Working-With-Data/06-non-relational/README.md) | [Jasmine](https://twitter.com/paladique)|
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| 07 | 使用 Python 工作 | [与数据打交道](../2-Working-With-Data/README.md) | 使用 Python 与 Pandas 等库进行数据探索的基础知识。建议对 Python 编程有基本的了解。 | [课程](../2-Working-With-Data/07-python/README.md) [视频](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) |
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## 需要帮忙！
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想贡献一份翻译吗？请阅读我们的 [翻译](TRANSLATIONS.md) 指南。
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想贡献一份翻译吗？请阅读我们的 [翻译](../TRANSLATIONS.md) 指南。
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## 其他课程
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