课程信息
4.5
1,847 个评分
251 个审阅
专项课程

第 3 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7 小时

建议:1 week of study, 4-6 hours...
可选语言

英语(English)

字幕:英语(English), 日语...

您将学到的内容有

  • Check

    Describe the basic data analysis iteration

  • Check

    Differentiate between various types of data pulls

  • Check

    Explore datasets to determine if data is appropriate for a project

  • Check

    Use statistical findings to create convincing data analysis presentations

您将获得的技能

Data AnalysisCommunicationInterpretationExploratory Data Analysis
专项课程

第 3 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7 小时

建议:1 week of study, 4-6 hours...
可选语言

英语(English)

字幕:英语(English), 日语...

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 6 小时

Managing Data Analysis

Welcome to Managing Data Analysis! This course is one module, intended to be taken in one week. The course works best if you follow along with the material in the order it is presented. Each lecture consists of videos and reading materials that expand on the lecture. I'm excited to have you in the class and look forward to your contributions to the learning community. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!...
Reading
19 个视频(共 144 分钟), 17 个阅读材料, 7 个测验
Video19 个视频
Data Analysis Iteration8分钟
Stages of Data Analysis1分钟
Six Types of Questions6分钟
Characteristics of a Good Question6分钟
Exploratory Data Analysis Goals & Expectations11分钟
Using Statistical Models to Explore Your Data (Part 1)13分钟
Using Statistical Models to Explore Your Data (Part 2)5分钟
Exploratory Data Analysis: When to Stop6分钟
Making Inferences from Data: Introduction5分钟
Populations Come in Many Forms4分钟
Inference: What Can Go Wrong7分钟
General Framework8分钟
Associational Analyses10分钟
Prediction Analyses10分钟
Inference vs. Prediction12分钟
Interpreting Your Results10分钟
Routine Communication in Data Analysis6分钟
Making a Data Analysis Presentation5分钟
Reading17 个阅读材料
Pre-Course Survey10分钟
Course Textbook: The Art of Data Science10分钟
Conversations on Data Science10分钟
Data Science as Art10分钟
Epicycles of Analysis10分钟
Six Types of Questions10分钟
Characteristics of a Good Question10分钟
EDA Check List10分钟
Assessing a Distribution10分钟
Assessing Linear Relationships10分钟
Exploratory Data Analysis: When Do We Stop?10分钟
Factors Affecting the Quality of Inference10分钟
A Note on Populations10分钟
Inference vs. Prediction10分钟
Interpreting Your Results10分钟
Routine Communication10分钟
Post-Course Survey10分钟
Quiz7 个练习
Data Analysis Iteration10分钟
Stating and Refining the Question16分钟
Exploratory Data Analysis10分钟
Inference10分钟
Formal Modeling, Inference vs. Prediction10分钟
Interpretation10分钟
Communication10分钟
4.5
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

热门审阅

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创建者 ELMar 1st 2017

A long course compared to others in the specialization, but a lot of great material. Very well presented, the instructors know how to present this material and make it easy to grasp and understand.

创建者 STNov 23rd 2016

The course is full of the cases and the real life examples coupled with the theory background. Its very simple to understand and the course will definitely be of an value for people looking for

讲师

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Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Brian Caffo, PhD

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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