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

4.4
étoiles
2,318 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: https://www.youtube.com/watch?v=9BIYmw5wnBI Course cover image by Jonathan Gross. Creative Commons BY-ND https://flic.kr/p/q1vudb...
Points forts
Statistics review

(44 avis)

Meilleurs avis

SM

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.

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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201 - 225 sur 280 Avis pour Data Science in Real Life

par TCHUENTE D

19 oct. 2016

par Gustavo V

13 avr. 2019

par Deepak G

28 juin 2016

par Sangeeta N

21 févr. 2021

par Chris C

22 nov. 2017

par Jomo C

28 janv. 2018

par Rorie D

20 avr. 2016

par Navneet W

10 sept. 2020

par Brian N

10 avr. 2018

par Paul C

4 nov. 2016

par Paulose B

31 oct. 2016

par JERRY O

22 janv. 2020

par SANTOSH K R

7 janv. 2017

par Hubertus H

27 janv. 2017

par Nachum S

13 juil. 2018

par Setia B

6 déc. 2017

par Jeffery T

30 nov. 2017

par Angel S

17 janv. 2016

par Venuprasad R

5 janv. 2016

par Rui R

18 juin 2017

par SARAVANAN.V

20 juin 2020

par Deepa F P

5 sept. 2017

par SARMAD H

5 août 2020

par R.K.Suriyakumar

7 juin 2020

par ECE- R G

13 juil. 2020