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

4.4
stars
2,244 ratings
269 reviews

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

SM
Aug 19, 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 11, 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 of 268 Reviews for Data Science in Real Life

By Siddharth T

Apr 3, 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.

By Vivek V

Mar 8, 2020

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

By Sheila O

Jan 2, 2021

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

By Karthik S N

May 1, 2016

Good concepts - apply to anyone new to data science.

Lot of good 'read further' links and materials. Learnt a lot.

By Barnali G

Apr 1, 2021

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

By Andrew W

Nov 2, 2017

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

By Boris L

Oct 5, 2015

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

By Udaypal S N

Nov 25, 2017

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

By Challenger

Dec 15, 2020

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

By Natalya K

Jul 8, 2017

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

By Warren L

May 5, 2017

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

By Morie H H K

Aug 31, 2020

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

By Debasish M

Feb 2, 2017

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

By TCHUENTE D

Oct 19, 2016

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

By Gustavo V

Apr 13, 2019

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

By Deepak G

Jun 28, 2016

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

By Sangeeta N

Feb 21, 2021

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

By Chris C

Nov 22, 2017

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

By Jomo C

Jan 28, 2018

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

By Rorie D

Apr 20, 2016

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

By Navneet W

Sep 10, 2020

On of the best courses of Data science on Coursera.

By Brian N

Apr 10, 2018

Good for introduction in Data Science Process

By Paul C

Nov 4, 2016

A solid course with lots of practical advice.

By Paulose B

Oct 31, 2016

Short session need more handson excercise

By JERRY O

Jan 22, 2020

Good course with vibrant instructors.