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

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2,262 Bewertungen
272 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: 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 Bewertungen)

Top-Bewertungen

SM
19. Aug. 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
11. Nov. 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 274 Bewertungen für Data Science in Real Life

von Elitza K

5. Mai 2021

well structured, very clear and vital examples; extremely useful and practical recommendations. I've enjoyed the course and have learned a lot of short time!

von Manjunatha V M

7. Jan. 2017

Clear explanation of various concepts with good examples. Of course, reference to some cool cartoons from time to time made the concepts more memorable!

von Carlos J

20. Sep. 2017

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

von Alfredo O G

14. Nov. 2016

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

von Gurpreet K K

2. Aug. 2021

The lecturer has obvisously been through all the issues and learnt about them, perhaps first hand. It was a delight! Thanks so much!

von Edgar A C V

14. Mai 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!!!

von Gautam R

17. Mai 2020

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

von Emmanuelle M

10. Okt. 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

31. März 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

8. Juli 2019

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

von Roque A

23. Sep. 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

29. Mai 2020

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

von William K

4. Jan. 2017

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

von Alberto D E

14. Mai 2018

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

von S R

10. Nov. 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

14. Dez. 2018

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

von Matthias L

27. Aug. 2017

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

von Sambit K D

8. Dez. 2020

The instructor Brian Caffo is very knowledgeable and great presenter. Has real practical examples.

von Bart P

12. Apr. 2019

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

von Paul S

28. Jan. 2017

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

von Mauricio L

22. Juni 2019

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

von Ayna M

13. Dez. 2017

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

von Abid C

10. Juli 2017

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

von Ramkumar

1. Juli 2017

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

von Aedrian A

13. Jan. 2021

I enjoyed taking this course and I think that it delivers on what it promises on the title.