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# Introduction to Data Science
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# 데이터 과학의 입문
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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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> 이미지 출처: <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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이 레슨에서, 당신은 어떻게 데이터 과학이 정의되었는지 발견하고 데이터 과학자에게 있어서 필히 고려해야만 하는 윤리적 사항들에 대하여 배울 것입니다. 당신은 또한 데이터가 어떻게 정의되었는지와, 데이터 과학 학습 영역에서의 중심인 약간의 통계와 확률에 대하여 배울 것입니다.
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### Topics
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1. [Defining Data Science](01-defining-data-science/README.md)
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2. [Data Science Ethics](02-ethics/README.md)
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3. [Defining Data](03-defining-data/README.md)
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4. [Introduction to Statistics and Probability](04-stats-and-probability/README.md)
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### 토픽
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### Credits
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1. [데이터 과학 정의하기](01-defining-data-science/README.md)
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2. [데이터 과학에서의 윤리](02-ethics/README.md)
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3. [데이터 정의하기](03-defining-data/README.md)
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4. [통계와 확률에 대한 소개](04-stats-and-probability/README.md)
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These lessons were written with ❤️ by [Nitya Narasimhan](https://twitter.com/nitya) and [Dmitry Soshnikov](https://twitter.com/shwars).
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### 출처
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이 강의들은 [Nitya Narasimhan](https://twitter.com/nitya)[Dmitry Soshnikov](https://twitter.com/shwars)에 의해 쓰여졌음❤️

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