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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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226 - 250 von 274 Bewertungen für Data Science in Real Life

von Gonzalo G A

16. Dez. 2016

It's sometimes difficult to follow professors beacuse they take for granted information about the examples they use that is not evident for the learners. They should take a minute to explain a little bit more what the examples consist of and what are the charts they show. As it happens when Brian Caffo explains the blocking adjustments part.

von Cauri J

4. Juli 2017

I found this course used a lot of jargon without explanation. It seems like the instructor understands the content so well that he assumes a level of knowledge from students that do not match the expectations of the rest of the content in this track. At the same time I found the content well presented.

von Michail C

17. Juli 2019

This course is an excellent effort to document the issues faced in real-life data science. However, the flow of the videos seems to be a bit confusing and some of the content is explained in a weird manner.

von Daniel C d F

5. Dez. 2016

I missed several concepts to better understand some of the discussions and explanations. It was valid, but I think the statistics background should be better explored.

von Peter L

14. Aug. 2018

The course is valuable but highly focussed on scientific applications (inference) and less on business application (i.e. prediction). I hoped for a more even mix.

von Astolfo

5. Juli 2020

It was good, but the content is harder to understand in this course.

I would prefer a similar format and emphasis as the other two last courses.

von Sean H

24. Nov. 2015

The video quality and content were good. Unfortunately, there were a lot of spelling errors and grammatical mistakes in the written portions.

von Chong K M

18. März 2018

Very difficult and time consuming course which contains a lot of technical words and jargon. Not recommended for the average beginner.

von Jean-Michel M

22. Feb. 2019

I would drop some of the cartoons. They are funny but they seem to distract Bryan and overall it's distracting for us students too.

von PAVITHRA.T

28. Juli 2020

First of all it's too tough to understand but day by day I understood something I got it ..tq.it is very helpful for my studies

von Rong-Rong C

14. Dez. 2017

There is a lot of technical jargon covered which made the course more challenging than the other courses in the series.

von Alberto M B

20. März 2019

It wasn't as focus on Managing Data Scientists as I was expecting, but rather focus on tips for Data Scientist.

von Marco A P

2. Jan. 2017

Much theorical with few examples. Could incorporate examples outside the health world as well.

von Giovany G

15. Juli 2020

I would prefer that the examples be expressed with statistical and mathematical calculations

von Gilson F

2. Aug. 2019

Não gostei muito da didatica do instrutor e os slides não ajudam no entendimento

von emilio z

6. Juni 2017

Explanations in videos qere not very clear nor very well connecetd with the Quiz

von Christopher L

3. Mai 2018

Would have liked a bit more examples and math in some cases. Others were fine.

von Ioannis L

9. Apr. 2017

A bit less engaging than the other parts of the Executive Data Science course.

von Patricia S

2. Jan. 2020

good content but could be simplified and presented in a more focused man

von Gowtham V

2. Mai 2020

Would like to have simpler examples to understand some of the concepts.

von Amal L C

16. März 2017

It was quite hard with all the statistical jargon. Too much theory.

von Poon F

30. Jan. 2018

This class has more useful materials than previous ones.

von Manas B

10. Mai 2016

Relevant materials, but lecture delivery is rather dry,

von Matej K

1. Mai 2018

Sometimes it was hard to understand what's going on.

von Angelina

2. Apr. 2019

The material is too long and boring.