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返回到 数据科学速成课

学生对 约翰霍普金斯大学 提供的 数据科学速成课 的评价和反馈

8,015 个评分


By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials. This is a focused course designed to rapidly get you up to speed on the field of data science. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward. After completing this course you will know. 1. How to describe the role data science plays in various contexts 2. How statistics, machine learning, and software engineering play a role in data science 3. How to describe the structure of a data science project 4. Know the key terms and tools used by data scientists 5. How to identify a successful and an unsuccessful data science project 3. The role of a data science manager Course cover image by r2hox. Creative Commons BY-SA:
Basic course

(76 条评论)

Well taught

(48 条评论)



Sep 9, 2017

This is a great starter course for data science. My learning assessment is usually how well I can teach it to someone else. I know I have a better understanding now, than I did when I started.


Aug 27, 2016

Is really hard to summarize the potential of Data Science and being clear, but I think that the instructors have done their best, so that we can achieve the most from the Course.

Great Job!


1 - 数据科学速成课 的 25 个评论(共 1,472 个)

创建者 Sven M

Sep 18, 2016

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Sep 13, 2017

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Apr 4, 2019

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Dec 28, 2017

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Nov 27, 2019

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Aug 15, 2016

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Jun 5, 2020

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Oct 5, 2021


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Mar 14, 2019

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May 7, 2016

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Sep 16, 2017

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Nov 19, 2015

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Sep 11, 2016

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May 23, 2016

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Feb 19, 2021

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