生活中的数据科学

Data Science in Real Life

Part of a 5-course series, the Executive Data Science Specialization

约翰霍普金斯大学

Coursera

计算机

简单(初级)

6 小时

课程概况

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:

Course cover image by Jonathan Gross. Creative Commons BY-ND https://flic.kr/p/q1vudb

你将学到什么

Describe common pitfalls in communicating data analyses

Identify strengths and weaknesses in experimental designs

Learn novel solutions for managing data pulls

Understand a typical day in the life of a data analysis manager

课程大纲

Introduction, the perfect data science experience

This course is one module, intended to be taken in one week. Please do the course roughly in the order presented. Each lecture has reading
and videos. Except for the introductory lecture, every lecture has a 5 question quiz; get 4 out of 5 or better on the quiz.

声明:MOOC中国发布之课程均源自下列机构,版权均归他们所有。本站仅作报道收录并尊重其著作权益,感谢他们对MOOC事业做出的贡献!(排名不分先后)
  • Coursera
  • edX
  • OpenLearning
  • FutureLearn
  • iversity
  • Udacity
  • NovoEd
  • Canvas
  • Open2Study
  • Google
  • ewant
  • FUN
  • IOC-Athlete-MOOC
  • World-Science-U
  • Codecademy
  • CourseSites
  • opencourseworld
  • ShareCourse
  • gacco
  • MiriadaX
  • JANUX
  • openhpi
  • Stanford-Open-Edx
  • 网易云课堂
  • 中国大学MOOC
  • 学堂在线
  • 顶你学堂
  • 华文慕课
  • 好大学在线CnMooc
  • 以及更多...

© 2008-2018 MOOC.CN 慕课改变你,你改变世界