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返回到 生活中的数据科学

生活中的数据科学, 约翰霍普金斯大学

4.4
1,442 个评分
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166 个审阅

课程信息

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses. This is a focused course designed to rapidly get you up to speed on doing data science in real life. 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 how to: 1, Describe the “perfect” data science experience 2. Identify strengths and weaknesses in experimental designs 3. Describe possible pitfalls when pulling / assembling data and learn solutions for managing data pulls. 4. Challenge statistical modeling assumptions and drive feedback to data analysts 5. Describe common pitfalls in communicating data analyses 6. Get a glimpse into a day in the life of a data analysis manager. The course will be taught at a conceptual level for active managers of data scientists and statisticians. Some key concepts being discussed include: 1. Experimental design, randomization, A/B testing 2. Causal inference, counterfactuals, 3. Strategies for managing data quality. 4. Bias and confounding 5. Contrasting machine learning versus classical statistical inference Course promo: https://www.youtube.com/watch?v=9BIYmw5wnBI Course cover image by Jonathan Gross. Creative Commons BY-ND https://flic.kr/p/q1vudb...
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Statistics review
（44 个审阅）

热门审阅

创建者 SM

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Aug 20, 2017

A very good and concise course that helps to understand the basics of the Data Science and its applications. The examples are very relevant and helps to understand the topic easily.

创建者 ES

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Nov 12, 2017

Highly educational course on the realities of data analysis. Many good tips for your own analyses as well as for managing others responsible for coherent and accurate analyses.

筛选依据：

167 个审阅

创建者 Jason Goungo

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Mar 18, 2019

Very informative and a good introduction into the aspects faced while doing Data Science!

创建者 Hector Raul Colonia Coral

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Mar 17, 2019

thanks!

创建者 BAHAR AĞMA

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Feb 24, 2019

It is a helpful course about a statistical area. I recommend it.

创建者 Jean-Michel Maltais

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Feb 22, 2019

I would drop some of the cartoons. They are funny but they seem to distract Bryan and overall it's distracting for us students too.

创建者 Neil Newman

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Feb 17, 2019

Good overview of the reality of the challenges in data science. A glaring miss from my perspective was any real focus on the challenges of ML/AI based analysis. This module was really focused on traditional statistical modeling

创建者 Liping LIN

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Jan 29, 2019

This is a recommended course where you understand what are the requirements for a data engineer, data manager and data scientis

创建者 Ng Thian Choon

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Jan 27, 2019

Good learning

创建者 Alzum Shahadat Miazee

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Jan 20, 2019

It's an excellent course. I have learnt a lot.

创建者 Shafeeq Shas

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Jan 08, 2019

Not that engaging content.Too much theoretical approach.

创建者 Kim Kirkpatrick Rigg

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Dec 23, 2018

GREAT COURSE!!!

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