课程信息
4.4
1,322 个评分
157 个审阅
专项课程

第 4 门课程(共 5 门),位于

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为6 小时

建议:1 week of study, 4-6 hours...
可选语言

英语(English)

字幕:英语(English)...

您将学到的内容有

  • Check

    Describe common pitfalls in communicating data analyses

  • Check

    Identify strengths and weaknesses in experimental designs

  • Check

    Learn novel solutions for managing data pulls

  • Check

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

您将获得的技能

StatisticsData ScienceData AnalysisData Management
专项课程

第 4 门课程(共 5 门),位于

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为6 小时

建议:1 week of study, 4-6 hours...
可选语言

英语(English)

字幕:英语(English)...

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 5 小时

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....
Reading
22 个视频(共 160 分钟), 10 个阅读材料, 6 个测验
Video22 个视频
Data science in the ideal versus real life Part 14分钟
Data science in the ideal versus real life Part 23分钟
Examples7分钟
Machine Learning vs. Traditional Statistics Part 114分钟
Machine Learning vs. Traditional Statistics Part 23分钟
Managing the Data Pull11分钟
Experimental design and observational analysis10分钟
Causality part 18分钟
Causality Part 29分钟
What Can Go Wrong?: Confounding5分钟
A/B Testing9分钟
Sampling bias and random sampling5分钟
Blocking and adjustment11分钟
Multiplicity6分钟
Effect size, significance, & modeling7分钟
Comparison with benchmark effects4分钟
Negative controls5分钟
Non-significance5分钟
Estimation Target is Relevant10分钟
Report writing8分钟
Version control4分钟
Reading10 个阅读材料
Pre-Course Survey10分钟
Course structure10分钟
Grading10分钟
The data pull is clean10分钟
The experiment is carefully designed10分钟
The experiment is carefully designed, things to do10分钟
Results of analyses are clear10分钟
The decision is obvious10分钟
The analysis product is awesome10分钟
Post-Course Survey10分钟
Quiz6 个练习
The Data Pull is Clean10分钟
The experiment is carefully designed principles10分钟
The experiment is carefully designed, things to do10分钟
Results of analyses are clear8分钟
The Decision is Obvious10分钟
The analysis product is awesome10分钟
4.4
157 个审阅Chevron Right
职业方向

50%

完成这些课程后已开始新的职业生涯
工作福利

83%

通过此课程获得实实在在的工作福利

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Statistics review
(44)
创建者 SMAug 20th 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 ESNov 12th 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.

讲师

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Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health
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Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

关于 Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

关于 Executive Data Science 专项课程

Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects. In four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects....
Executive Data Science

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