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

4.4
stars
2,143 ratings
253 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 19, 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 11, 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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26 - 50 of 252 Reviews for Data Science in Real Life

By Carlos J

Sep 20, 2017

Esta serie de cursos, es recomendable para iniciar en la carrera de Ciencia de Datos, conceptos claros, expuestos por catedráticos de primer nivel

By Alfredo O G

Nov 13, 2016

An amazing course for those who are not very familiar with statistics and a very refreshing perspective for those who actually knows statistics!

By Edgar A C V

May 14, 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 Gautam R

May 17, 2020

Wanted some practical examples - of calculating P values with sample set of data & analyzing/reporting on it with inference.

By Emmanuelle M

Oct 10, 2018

Great course, although, if you are not already working or have knowledge in this particular filed/topic, it is challenging.

By Michael A L

Mar 31, 2018

An excellent overview of the topic material without a lot of unnecessary clutter. Well-organized and -communicated. Kudos.

By Paulo B M d S

Jul 8, 2019

The authors really present real situation and challenges that data scientists face in their daily activities. Very good.

By Roque A

Sep 23, 2018

Very easy to follow with good examples. The focus on this course was on practicality and I really appreciated that

By Victor D R L

May 29, 2020

This is a very good course but challeging. There is just too many concepts, recommendations and ideas to tackle.

By William K

Jan 4, 2017

Excellent course. The material is good enough that will help me where to look for information, considerations, a

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 Ryan M S

Nov 10, 2019

I found this course to be the most enjoyable and knowledge benefiting of all the courses I've taken thus far.

By Elton K

Dec 14, 2018

Interesting for a Non-Data Science Executive despite some minor spelling errors in video transcripts.

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 pietbartolo

Apr 12, 2019

Very useful course! I really enjoyed the technical not so much the statistical part of the course.

By Paul S

Jan 28, 2017

Helpful tips for handling problems during the several life cycle stages of a Data Science project.

By Mauricio L

Jun 22, 2019

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

By Ayna M

Dec 13, 2017

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

By Abid C

Jul 10, 2017

It is not easy to make experience fell like "a simple" course, congratulation and thank-you .

By Ramkumar

Jul 1, 2017

This course was really good. Good articulation on randomization and why we do randomization.

By Christos G

Sep 1, 2017

Smartly selected topics for an executive course. Well balanced between theory and examples.

By Iuri V d J Q

Mar 7, 2016

Awesome feedback on real life situations where i managed to pass through on my current job.

By Vikas K T

Apr 26, 2016

This is really a very nice course for learning data science in solving real life problems.

By Jason G

Mar 17, 2019

Very informative and a good introduction into the aspects faced while doing Data Science!

By Gabriela E L M

May 8, 2017

Very punctual practical and applicable information about do's and don'ts for DS projects.