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Learner Reviews & Feedback for Data Science in Real Life by Johns Hopkins University

4.4
1,547 ratings
185 reviews

About the Course

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses. This is a focused course designed to rapidly get you up to speed on doing data science in real life. 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 how to: 1, Describe the “perfect” data science experience 2. Identify strengths and weaknesses in experimental designs 3. Describe possible pitfalls when pulling / assembling data and learn solutions for managing data pulls. 4. Challenge statistical modeling assumptions and drive feedback to data analysts 5. Describe common pitfalls in communicating data analyses 6. Get a glimpse into a day in the life of a data analysis manager. The course will be taught at a conceptual level for active managers of data scientists and statisticians. Some key concepts being discussed include: 1. Experimental design, randomization, A/B testing 2. Causal inference, counterfactuals, 3. Strategies for managing data quality. 4. Bias and confounding 5. Contrasting machine learning versus classical statistical inference Course promo: https://www.youtube.com/watch?v=9BIYmw5wnBI Course cover image by Jonathan Gross. Creative Commons BY-ND https://flic.kr/p/q1vudb...
Highlights
Statistics review
(44 Reviews)

Top reviews

SM

Aug 20, 2017

A very good and concise course that helps to understand the basics of the Data Science and its applications. The examples are very relevant and helps to understand the topic easily.

ES

Nov 12, 2017

Highly educational course on the realities of data analysis. Many good tips for your own analyses as well as for managing others responsible for coherent and accurate analyses.

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76 - 100 of 184 Reviews for Data Science in Real Life

By Alberto D E

May 14, 2018

A crash course on what can go wrong in real Data Science projects, and how to improve your chances of success.

By Gabriel U U

May 26, 2018

Great Learning experience

By Daniel M M

Sep 10, 2017

A bit extense but very well simplified for non experts in Statistics.

By Matthias L

Aug 27, 2017

This is very useful and a good primer on what to look out for when working in real life. Well done!

By ellen w

Aug 07, 2017

Excellent!

By JOSÉ B A F

Feb 12, 2018

I learned everything I hoped to learn

By Bauyrzhan S

Jun 13, 2018

Perfect

By SagarSrinivas

Oct 03, 2017

It's too good!.

By MARIO L

May 06, 2018

Challenging

By Sateesh K R

Mar 11, 2016

Excellent overview course on Data Science

By Sandip M

Aug 20, 2017

A very good and concise course that helps to understand the basics of the Data Science and its applications. The examples are very relevant and helps to understand the topic easily.

By Edgar A C V

May 15, 2018

I just finished this course but I cant enroll to the last one (I have 4/5 course in this moment). Can you please help me?? thanks!!!

By Ajay P

Feb 21, 2016

Excellent course, material and superior teaching.

By olive

Sep 27, 2016

Excellent experience - I cant wait for the capstone project.

By Ben T

Dec 28, 2016

Highly educative and recommended

By Asif J

Mar 27, 2017

this course gave good foundation.

By Ayna M

Dec 13, 2017

Loved all the examples to explain the terms like confounding, blocking, surrogate variables etc.

By bojana m

Jun 26, 2016

Necessities: practical tools and techniques for managing real life issues with data cleanliness, interpretation of results, report writing, version control. All of them complete necessities for real life commercial projects.

By Vijai K S

Feb 10, 2016

Short yet nice. Gave me a lot of insights on what can and can't be done.

By Wladimir R

Sep 30, 2018

Excellent

By Jose A R N

Sep 30, 2016

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career.

Please, take a look at my LinkedIn profile: https://www.linkedin.com/in/joseantonio11

I did this course to get new knowledge about Big Data and better understand the technology and your practical applications.

The course was excellent and the classes well taught by teachers.

Congratulations to Coursera team and Instructors.

Regards

By Georgios P

May 06, 2019

Very good introductory topics!

By Omid F

May 10, 2019

Thank you very much for your excellent course.

Best Regards

Omid Faseli

By Yonathan M P

Jun 08, 2019

Great course!!!!! Tons of useful insights!

By Mauricio L

Jun 22, 2019

Great course. It delivers a fantastic framework to assess the process of successful Data Science.