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

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


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.

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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176 - 200 von 274 Bewertungen für Data Science in Real Life

von Nishant J

5. März 2018

Examples used in this course are related to Lifescience and candidates like me find it difficult to correlate. It would be beneficial to use some common life examples.

von Kian G L

13. Aug. 2016

Is good to have some data science background to enroll in this course, overall still good to learn and get the hint of how real life data scientist life is.


9. Mai 2018

Good course - I'm now confident to oversee an end-to-end data science experiment. Some interactivity would make this the perfect overview of data science.

von Reginald D F

23. Dez. 2017

I like that this course examples the many ways an experiment/analysis can go wrong and how to address these issues. Very practical for the practitioner.

von Kitven L

30. Dez. 2020

Many real life examples but in the courses the instructor introduced some new concepts which could be useful if get into more details of them.

von Siddharth T

3. Apr. 2016

Again a course with depth in content but the presentation of the course could improve , it seems a bit patchy and pre-reads would help.

von Vivek V

8. März 2020

A very well crafted course, with apt messaging and good assessments. Was able to learn a lot about the nuances of Data Science

von Sheila O

2. Jan. 2021

Materials and lectures were really helpful. Would like to have seen a bit more on prediction analysis in real life.

von Karthik S N

1. Mai 2016

Good concepts - apply to anyone new to data science.

Lot of good 'read further' links and materials. Learnt a lot.

von Barnali G

1. Apr. 2021

Great from an overview perspective. Certainly learnt the overall basics as I was hoping to be able to.

von Andrew W

2. Nov. 2017

Great examples and explanations of real cases, very helpful for general understanding of concepts.

von Boris L

5. Okt. 2015

Very nice overview of what can go wrong in a data science project and what to pay attention to.

von Koshan E

8. Juli 2021

A very good and interesting course that gives you a good stepping stone regarding Data Science

von Udaypal S N

25. Nov. 2017

Need more focus on other industries like Telecom, Banking, Manufacturing, Semi-Conductor, etc.

von Challenger

15. Dez. 2020

Gives enough understanding of data science in related fields, but course is complicaed enough

von Natalya K

8. Juli 2017

A bit difficult to understand compared with other course of the specialization, but useful

von Warren L

5. Mai 2017

Appreciated the anecdotes as they allowed me to remember the learnings in context

von Morie H H K

31. Aug. 2020

Good for the start but need more insight explanations with hands-on practicals

von Debasish M

2. Feb. 2017

Practical approach and gotchas to consider for doing data science in real life


19. Okt. 2016

good course, but focus more on inferential analysis than predictive analysis

von Gustavo V

13. Apr. 2019

Help me understand what can I expect from a real data science project.

von Deepak G

28. Juni 2016

Quality of this course is better than the rest of the specialization.

von Sangeeta N

21. Feb. 2021

This gives the basics of Data Science that one needs to lead a team

von Chris C

22. Nov. 2017

A little difficult overall but had some key points to take away.

von Jomo C

28. Jan. 2018

Good course, Longer than expected. Very satisfying at the end