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Kursteilnehmer-Bewertung und -Feedback für Data Science in Real Life von Johns Hopkins University

1,993 Bewertungen
235 Bewertungen

Über den Kurs

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: Course cover image by Jonathan Gross. Creative Commons BY-ND
Statistics review
(44 Bewertungen)



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.


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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26 - 50 von 235 Bewertungen für Data Science in Real Life

von Gautam R

May 17, 2020

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

von 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.

von Michael A L

Mar 31, 2018

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

von Paulo B M d S

Jul 08, 2019

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

von Roque A

Sep 24, 2018

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

von 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.

von William K

Jan 04, 2017

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

von 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.

von 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.

von Elton K

Dec 14, 2018

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

von 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!

von pietbartolo

Apr 12, 2019

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

von Paul S

Jan 28, 2017

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

von Mauricio L

Jun 22, 2019

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

von Ayna M

Dec 13, 2017

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

von Abid C

Jul 10, 2017

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

von Ramkumar

Jul 01, 2017

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

von Christos G

Sep 01, 2017

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

von Iuri V d J Q

Mar 08, 2016

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

von vikas k

Apr 27, 2016

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

von Jason G

Mar 18, 2019

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

von Gabriela E L M

May 08, 2017

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

von Paul H

Jan 04, 2017

Lots of useful tips. Great overview spanning data science pitfalls. Impressively concise.

von Antonio P L

Dec 31, 2016

Fantastic Course for people who want to know the details to do great analysis and reports

von Felix E R P

Jun 15, 2016

Good review on how to work and interact with the team during the data analysis pipeline!