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Avis et commentaires pour d'étudiants pour Data Science in Real Life par Université Johns-Hopkins

2,330 évaluations

À propos du cours

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
Points forts
Statistics review

(44 avis)

Meilleurs avis


19 août 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 sur 281 Avis pour Data Science in Real Life

par Manish J

19 janv. 2021

Gives directions on how to deal with a situation where a clear conclusion may not be forthcoming from the analysis--- a situation that more often than not is likely to hold true in real world

par Dr D M

29 juil. 2020

This course is very interesting and worthwhile. we are living with data in our real life. good lectures. thanks to all team.


par Federico J D F

9 sept. 2020

The course was very interesting and complete. The lectures were interesting as well. The reading material could be improved by adding more articles to reinforce the theory and examples.

par Charissa B

11 janv. 2021

Helpful ideas to consider and use when managing a team of data scientists, especially helpful are the principles for dealing with on-the-ground data science work (vs ideal environments)

par Lai Y W @ L Y W

21 août 2020

Slightly difficult for non data science background people, but is manageable to have a dip into this course and stimulate a "real life" experiences shared by course insructor.

par Yani

27 oct. 2016

Dr.Caffo is really well-versed with his field but I feel like concepts should be given more concrete examples so that they seem more interesting. Respect him all the way!

par Nishant J

5 mars 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.

par Kian G L

13 août 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.

par Reginald D F

23 déc. 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.

par Kitven L

30 déc. 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.

par Siddharth T

3 avr. 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.

par Vivek V

8 mars 2020

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

par Sheila O

2 janv. 2021

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

par 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.

par Adeyinka O

30 nov. 2021

Content is rich, seem like so small but detailed and require good concentration to enjoy the quizes with ease

par Barnali G

1 avr. 2021

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

par Andrew W

2 nov. 2017

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

par Boris L

5 oct. 2015

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

par Koshan E

8 juil. 2021

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

par Udaypal S N

25 nov. 2017

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

par Challenger

15 déc. 2020

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

par Natalya K

8 juil. 2017

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

par Warren L

5 mai 2017

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

par Morie K

31 août 2020

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