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Voltar para Ciência de Dados na Vida Real

Comentários e feedback de alunos de Ciência de Dados na Vida Real da instituição Universidade Johns Hopkins

4.4
estrelas
1,671 classificações
190 avaliações

Sobre o curso

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...
Destaques
Statistics review
(44 avaliações)

Melhores avaliações

SM

Aug 20, 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

Nov 12, 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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126 — 150 de {totalReviews} Avaliações para o Ciência de Dados na Vida Real

por Natalya K

Jul 08, 2017

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

por Warren L

May 05, 2017

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

por Debasish M

Feb 02, 2017

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

por TCHUENTE D

Oct 19, 2016

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

por Gustavo V

Apr 14, 2019

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

por Deepak G

Jun 28, 2016

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

por Chris C

Nov 22, 2017

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

por Jomo C

Jan 28, 2018

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

por Rorie D

Apr 20, 2016

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

por Brian N

Apr 11, 2018

Good for introduction in Data Science Process

por Paul C

Nov 04, 2016

A solid course with lots of practical advice.

por Paulose B

Oct 31, 2016

Short session need more handson excercise

por JERRY O

Jan 22, 2020

Good course with vibrant instructors.

por SANTOSH K R

Jan 07, 2017

More real world examples are required

por Hubertus H

Jan 27, 2017

Good summary on experimental design.

por Nachum S

Jul 13, 2018

Good, a bit long for the material.

por Setia B

Dec 07, 2017

I really enjoyed the course :)

por Jeffery T

Dec 01, 2017

Good course for managers

por Angel S

Jan 17, 2016

Pretty useful course

por Venuprasad R

Jan 05, 2016

Very practical views

por Rui R

Jun 18, 2017

Too much theory ...

por Deepa F P

Sep 05, 2017

Good content

por SATISH R

Jun 07, 2017

Great

por David T

Nov 14, 2016

Some good tips, nothing terribly new for those who have had a course in statistics. Materials made easy to digest. The variety from the 3 instructors was nice. Missed opportunity: to combine the best aspects from each. The course notes were either excerpts from R.Peng's books /blogs (good) or automated transcripts (complete with typical AI typos... "wait" instead of "weight"). Some lectures were repetitive from one course to another. Slides with examples were useful, slides with clip-art and comic stips less so. Tries to be something for everyone. Would be better to aim either at former DS analysts aspiring to be managers or seasoned managers trying to better understand DS.

por Robert A

Feb 04, 2016

Brian, Jeff, and Roger: Thank you very much for all the data science courses, really great. I generally rate them 5 stars. But for this one, I'm giving 3 stars, not because the content is not good (it is; it provides good practical and experiential information), but rather because the material seems repetitive at times either within the same course or with topics in the other courses. Also, the sequencing and lectures seem sometime a bit disjointed.

May I humbly suggest an idea: Integrate the key points of this course relating to real-world examples and the sharing of real-world experiences into one of the other courses.

Thank you.

Robert Al-Jaar, PhD

robert.aljaar@rassociates.biz