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

4.4
étoiles
2,300 évaluations
278 avis

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

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

par Gustavo V

13 avr. 2019

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

par Deepak G

28 juin 2016

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

par Sangeeta N

21 févr. 2021

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

par Chris C

22 nov. 2017

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

par Jomo C

28 janv. 2018

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

par Rorie D

20 avr. 2016

great approach, thanks. A few typos, but otherwise great.

par Navneet W

10 sept. 2020

On of the best courses of Data science on Coursera.

par Brian N

10 avr. 2018

Good for introduction in Data Science Process

par Paul C

4 nov. 2016

A solid course with lots of practical advice.

par Paulose B

31 oct. 2016

Short session need more handson excercise

par JERRY O

22 janv. 2020

Good course with vibrant instructors.

par SANTOSH K R

7 janv. 2017

More real world examples are required

par Hubertus H

27 janv. 2017

Good summary on experimental design.

par Nachum S

13 juil. 2018

Good, a bit long for the material.

par Setia B

6 déc. 2017

I really enjoyed the course :)

par Jeffery T

30 nov. 2017

Good course for managers

par Angel S

17 janv. 2016

Pretty useful course

par Venuprasad R

5 janv. 2016

Very practical views

par Rui R

18 juin 2017

Too much theory ...

par SARAVANAN.V

20 juin 2020

Nice course 👍

par Deepa F P

5 sept. 2017

Good content

par SARMAD H

5 août 2020

Nice course

par R.K.Suriyakumar

7 juin 2020

its good

par ECE- R G

13 juil. 2020

Nothing