课程信息
4.4
4,149 个评分
•
816 个审阅
By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials. This is a focused course designed to rapidly get you up to speed on the field of data science. 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. 1. How to describe the role data science plays in various contexts 2. How statistics, machine learning, and software engineering play a role in data science 3. How to describe the structure of a data science project 4. Know the key terms and tools used by data scientists 5. How to identify a successful and an unsuccessful data science project 3. The role of a data science manager Course cover image by r2hox. Creative Commons BY-SA: https://flic.kr/p/gdMuhT...
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Executive Data Science专项课程
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100% 在线课程

立即开始，按照自己的计划学习。
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建议：1 week of study, 4-6 hours

完成时间大约为4 小时
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English

字幕：English, Chinese (Traditional), Russian, Turkish, Hindi

您将学到的内容有

  • Check
    Describe Data Science’s role in various contexts
  • Check
    Predict whether a Data Science project will be successful
  • Check
    Understand how Statistics and Machine Learning affect Data Science
  • Check
    Use the key terms used by data scientist

您将获得的技能

Data ScienceData AnalysisMachine LearningProject
Stacks

Course 1 of 5 in the

Executive Data Science专项课程
Globe

100% 在线课程

立即开始，按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Clock

建议：1 week of study, 4-6 hours

完成时间大约为4 小时
Comment Dots

English

字幕：English, Chinese (Traditional), Russian, Turkish, Hindi

教学大纲 - 您将从这门课程中学到什么

1

章节
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完成时间为 4 小时

A Crash Course in Data Science

This one-module course constitutes the first "week" of the Executive Data Science Specialization. This is an intensive introduction to what you need to know about data science itself. You'll learn important terminology and how successful organizations use data science....
Reading
11 个视频（共 78 分钟）, 8 个阅读材料, 9 个测验
Video11 个视频
About Your Instructors1分钟
What is Data Science?5分钟
Statistics by example activities11分钟
Machine learning, the basics13分钟
Machine learning further reading3分钟
What is Software Engineering for Data Science?6分钟
The Structure of a Data Science Project6分钟
The outputs of a data science experiment6分钟
The four secrets of a successful data science experiment14分钟
Data Scientist Toolbox5分钟
Separating Hype from Value3分钟
Reading8 个阅读材料
Specialization Textbook10分钟
Grading10分钟
Pre-Course Survey10分钟
Statistics by example activities10分钟
Machine learning10分钟
The outputs of a data science experiment10分钟
The four secrets of a successful data science experiment10分钟
Post-Course Survey10分钟
Quiz9 个练习
What is data science?2分钟
What is statistics good for?10分钟
Machine learning8分钟
Quiz: Software Engineering6分钟
Structure of a Data Science Project8分钟
The outputs of a data science experiment10分钟
Defining Success in Data Science8分钟
Data scientist toolbox8分钟
Separating hype from value8分钟
4.4
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26%

完成这些课程后已开始新的职业生涯
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83%

通过此课程获得实实在在的工作福利
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19%

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热门审阅

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Well taught
(48)
Basic course
(76)
创建者 SJ•Sep 10th 2017

This is a great starter course for data science. My learning assessment is usually how well I can teach it to someone else. I know I have a better understanding now, than I did when I started.

创建者 JM•Jan 2nd 2018

It is a very good course even if you are familiar with some aspects of data science work. If I have to make a suggestion, I would remark the importance of design skills during a data product,

讲师

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

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

常见问题

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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