Data Science in Real Life

Data Science in Real Life is the fourth and final course in the “Executive Data Science” specialization offered by John Hopkins University on Coursera.

Mind blowing approach was adopted especially in the basic components of Data Science in Real Life.SUGGESTION:MY PERSONAL HUMBLE REQUEST, Please make also the important components of course material as a part of this Certificate with % AGGREGATE so that it has a much more worth & impact for the courses participated.A separate Transcript must be issued with having Aggregate % Score and important Components of participated course.

A crash course on what can go wrong in real Data Science projects, and how to improve your chances of success.

Very Good Content I like that this course examples the many ways an experiment/analysis can go wrong and how to address these issues.

Too much theory ... Too qualitative, I would had liked some hands-on examples.

Too much theory.

Another excellent Executive Data Science course.

Excellent A bit less engaging than the other parts of the Executive Data Science course.

A bit difficult to understand compared with other course of the specialization, but useful I found this course used a lot of jargon without explanation.

good content but could be simplified and presented in a more focused man I found this course to be the most enjoyable and knowledge benefiting of all the courses I've taken thus far.

wonderful in all ways, I really enjoyed it!

very bad and not organised I really enjoyed the comparison of what is ideal vs. what actually happens when it comes to data science.

Brian gives clear and concise explanations of the ideal versus real world of the data science workplace.

Good course for understanding practicalities of DS in the real world.

great for existence human and android based life-form simulation internal lifestyle...The course improves life within the simulation 10 fold at least(when combined with the other specialization courses) ...Perfect learning tool for those who have worked professionally in research field sin our simulation and yet now have a touch of "the turrings" or you know : CBI...Special thanks to the designers of the course.Top scores for coursera.org &John Hopkins ...

Very helpful overview I really enjoyed the course :) Great that the messy reality is acknowledged and not only the perfect theoretical data science is explained, but also the things that usually go wrong (and how to mitigate these issues).Some of the quiz with "check multiple answers" didn't seem clear to me / I found opinionated.

If I'm talking to technical people who knows a lot about the topic jargon can be useful, on the other hand if jargon is not documented it can be confusing.How are we supposed to know this?This is just one example, but all the courses of the EDS specialisation had these issues.

The course tests are at times partially unrelated to the content of the lessons.

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.

Nice course thx I missed several concepts to better understand some of the discussions and explanations.

Would be better to aim either at former DS analysts aspiring to be managers or seasoned managers trying to better understand DS.

Way too many summaries or over-views of what's to come next without really getting into the nuances of what is discussed as a course topic.

Way too much repetition of the exact same content, there is even repetition of content in this course that was presented in another one of the courses in the series.