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Learner Reviews & Feedback for A Crash Course in Data Science by Johns Hopkins University

4.5
stars
7,579 ratings
1,433 reviews

About the 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...
Highlights
Basic course
(76 Reviews)
Well taught
(48 Reviews)

Top reviews

MD
Aug 27, 2016

Is really hard to summarize the potential of Data Science and being clear, but I think that the instructors have done their best, so that we can achieve the most from the Course.\n\nGreat Job!

SJ
Sep 9, 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.

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1226 - 1250 of 1,400 Reviews for A Crash Course in Data Science

By Manish K

Jul 2, 2020

Good Course

By Danish S

Feb 1, 2018

Good . Keep

By Kiru M N

Aug 19, 2017

Good course

By Ayush A

Nov 22, 2015

Nice one :)

By Beshan D

Jun 28, 2020

Course was

By Madeleine T

Dec 7, 2016

great to s

By Pulak M

Nov 21, 2016

elementary

By Maurice H

Feb 27, 2019

Too short

By 王俊杰

Oct 31, 2017

一个快速的入门介绍

By Naveen R M K

Nov 10, 2015

Good One.

By Efraime C

Sep 29, 2018

I

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e

s

By David C

May 6, 2020

Great!

By 陈逸凡

Oct 27, 2017

内容深度不足

By Mark G

Sep 27, 2016

Great\

By Aniket M

Jun 19, 2020

Great

By Pappu T 1

May 23, 2020

Great

By Himadri N B

Aug 2, 2020

Well

By Rohan J

Jun 26, 2020

cool

By Swarnava G

Aug 23, 2017

Nice

By Yakshdeep D

Apr 15, 2020

V

By AHMET E

Nov 28, 2017

t

By Naren

Mar 2, 2017

v

By Jatin P

Oct 19, 2015

G

By ram s

Mar 19, 2016

I want to give 3.5 stars but there is only option for 3 or 4.

Given that it's geared more towards wanna be managers in this field. I would have expected lot of case studies, and links to additional material for individual reading plus a mini write up or a project at the end.

For MOOCs to compete with a degree program or an onsite instruction few of the things I think that are needed are

Interviews with industry practitioners which is a big plus.

interviews/postings from people with similar background as the 90% of the MOOC students of this program who made it... this motivates the students from dropping from the middle of the course/specilization programs

links to additional articles that the students can read at leisure

writeup/project as assignments that the students can pursue and publish (not necessarily for grade but as a mind jogger)

One more thing that I think should help (not specific to this course) is that the student with the best grade should be offered one free course and think this will motivate the students to complete the courses.

By Nate A

Jan 5, 2016

I wanted to like this course but It felt entirely too academic in terms of both the subject matter and the way the specifics of "data science" are presented. The course content reminded me of my time a few years ago when I was enrolled in a Ph.D. program at a major Tier 1 research university. The professors were great, but the content was esoteric and incredibly focused on research based "data science" and less on business analytics or more practical applications of data science for the working professional. I felt myself re-watching the videos to try and understand the content because there were many instances where the professors' spoke about some fundamental aspect of data science but failed to provide some real world context. I liked the course but I would not recommend it as a crash course for the working professional, more like a crash course for someone who already has a degree in statistics/math/engineering who is looking to further their studies in an academic setting where research is the main goal.