A Crash Course in Data Science

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Description

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  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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 a…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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

Created by:  Johns Hopkins University
  • Taught by:  Jeff Leek, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Brian Caffo, PhD, Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Roger D. Peng, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
Basic Info Course 1 of 5 in the Executive Data Science Specialization Commitment 1 week of study, 4-6 hours Language English, Subtitles: Turkish, Russian, Chinese (Traditional) How To Pass Pass all graded assignments to complete the course. User Ratings 4.4 stars Average User Rating 4.4See what learners said 课程作业

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证书

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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.

Syllabus


WEEK 1


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.


11 videos, 8 readings expand


  1. Video: About Your Instructors
  2. 阅读: Specialization Textbook
  3. 阅读: Grading
  4. 阅读: Pre-Course Survey
  5. Video: What is Data Science?
  6. 阅读: Statistics by example activities
  7. Video: Statistics by example activities
  8. 阅读: Machine learning
  9. Video: Machine learning, the basics
  10. Video: Machine learning further reading
  11. Video: What is Software Engineering for Data Science?
  12. Video: The Structure of a Data Science Project
  13. 阅读: The outputs of a data science experiment
  14. Video: The outputs of a data science experiment
  15. 阅读: The four secrets of a successful data science experiment
  16. Video: The four secrets of a successful data science experiment
  17. Video: Data Scientist Toolbox
  18. Video: Separating Hype from Value
  19. 阅读: Post-Course Survey

Graded: What is data science?
Graded: What is statistics good for?
Graded: Machine learning
Graded: Quiz: Software Engineering
Graded: Structure of a Data Science Project
Graded: The outputs of a data science experiment
Graded: Defining Success in Data Science
Graded: Data scientist toolbox
Graded: Separating hype from value
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There are no frequently asked questions yet. Send an Email to info@springest.co.uk