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Learner Reviews & Feedback for Data Science in Real Life by Johns Hopkins University

4.5
stars
2,379 ratings

About the Course

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...
Highlights
Statistics review

(44 Reviews)

Top reviews

CB

Jan 11, 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)

LW

Aug 21, 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.

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201 - 225 of 289 Reviews for Data Science in Real Life

By Udaypal S N

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Nov 25, 2017

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

By Challenger

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Dec 15, 2020

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

By Natalia K

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Jul 8, 2017

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

By Warren L

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May 5, 2017

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

By Morie K

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Aug 31, 2020

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

By Debasish M

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Feb 2, 2017

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

By TCHUENTE D

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Oct 19, 2016

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

By Gustavo V

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Apr 14, 2019

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

By Deepak G

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Jun 28, 2016

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

By Sangeeta N

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Feb 21, 2021

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

By Chris C

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Nov 22, 2017

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

By Jomo C

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Jan 28, 2018

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

By Rorie D

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Apr 20, 2016

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

By Navneet W

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Sep 10, 2020

On of the best courses of Data science on Coursera.

By Brian N

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Apr 11, 2018

Good for introduction in Data Science Process

By Paul C

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Nov 4, 2016

A solid course with lots of practical advice.

By Paulose B

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Oct 31, 2016

Short session need more handson excercise

By JERRY O

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Jan 22, 2020

Good course with vibrant instructors.

By SANTOSH K R

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Jan 7, 2017

More real world examples are required

By Hubertus H

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Jan 27, 2017

Good summary on experimental design.

By Nachum S

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Jul 13, 2018

Good, a bit long for the material.

By Setia B

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Dec 7, 2017

I really enjoyed the course :)

By Jeffery T

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Dec 1, 2017

Good course for managers

By Angel S

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Jan 17, 2016

Pretty useful course

By Venuprasad R

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Jan 5, 2016

Very practical views