課程信息
4.4
1,322 個評分
157 個審閱
專項課程

第 4 門課程(共 5 門),位於

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為6 小時

建議:1 week of study, 4-6 hours...
可選語言

英語(English)

字幕:英語(English)...

您將學到的內容有

  • 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

您將獲得的技能

StatisticsData ScienceData AnalysisData Management
專項課程

第 4 門課程(共 5 門),位於

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為6 小時

建議:1 week of study, 4-6 hours...
可選語言

英語(English)

字幕:英語(English)...

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 5 小時

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 個視頻(共 160 分鐘), 10 個閱讀材料, 6 個測驗
Video22 個視頻
Data science in the ideal versus real life Part 14分鐘
Data science in the ideal versus real life Part 23分鐘
Examples7分鐘
Machine Learning vs. Traditional Statistics Part 114分鐘
Machine Learning vs. Traditional Statistics Part 23分鐘
Managing the Data Pull11分鐘
Experimental design and observational analysis10分鐘
Causality part 18分鐘
Causality Part 29分鐘
What Can Go Wrong?: Confounding5分鐘
A/B Testing9分鐘
Sampling bias and random sampling5分鐘
Blocking and adjustment11分鐘
Multiplicity6分鐘
Effect size, significance, & modeling7分鐘
Comparison with benchmark effects4分鐘
Negative controls5分鐘
Non-significance5分鐘
Estimation Target is Relevant10分鐘
Report writing8分鐘
Version control4分鐘
Reading10 個閱讀材料
Pre-Course Survey10分鐘
Course structure10分鐘
Grading10分鐘
The data pull is clean10分鐘
The experiment is carefully designed10分鐘
The experiment is carefully designed, things to do10分鐘
Results of analyses are clear10分鐘
The decision is obvious10分鐘
The analysis product is awesome10分鐘
Post-Course Survey10分鐘
Quiz6 個練習
The Data Pull is Clean10分鐘
The experiment is carefully designed principles10分鐘
The experiment is carefully designed, things to do10分鐘
Results of analyses are clear8分鐘
The Decision is Obvious10分鐘
The analysis product is awesome10分鐘
4.4
157 個審閱Chevron Right
職業方向

50%

完成這些課程後已開始新的職業生涯
工作福利

83%

通過此課程獲得實實在在的工作福利

熱門審閱

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Statistics review
(44)
創建者 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.

創建者 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.

講師

Avatar

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

關於 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....

關於 Executive Data Science 專項課程

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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