Online Course
A Crash Course in Data Science
Johns Hopkins University via Coursera
Found in
Data Science
- Provider Coursera
- Cost Free Online Course (Audit)
- Session Finished
- Language English
- Certificate Paid Certificate Available
- Duration 1 weeks long
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Overview
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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
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
Syllabus
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.
-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.
Taught by
Jeff Leek, Brian Caffo and Roger Peng
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Reviews for Coursera's A Crash Course in Data Science Based on 20 reviews
- 5 stars 25%
- 4 stars 20%
- 3 stars 35%
- 2 stars 10%
- 1 stars 10%
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Write a review- 1
Gregory S
by
Gregory
completed this course.
A Crash Course in Data Science is a succinct, one-week overview of the field of data science produced by the same team from John Hopkins University that produced Coursera’s data science specialization. It is the first course in the “Executive Data Science” specialization, a data science track aimed at non-technical people like business managers. The course defines data science and then discusses different aspects of data science like statistics, machine learning and the structure, output and success metrics for data science projects. Grading is based on a handful of short multiple-choice comp…
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Dissipate D
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Dissipate
completed this course.
This course provides a peek into what data science is like, but only gives a general picture in relation to some aspects. The topics were fine, but the quality of lecturing is bad with the lecturers being unclear with vague phrases. I would probably have learnt more spending the time reading an introductory book to data science.
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Andrew
completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.
Good high level overview -- lame that the quizzes are locked, there is essentially nothing to give you a sense of accomplishing anything unless you pay.
Did whole course in one sitting. Will review whole specialization.
Did whole course in one sitting. Will review whole specialization.
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Abu
is taking this course right now, spending 2 hours a week on it and found the course difficulty to be medium.
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