学生对 约翰霍普金斯大学 提供的 生活中的数据科学 的评价和反馈

OK

Some of the material here was repeated from other courses but overall I felt this was my favorite course in the series. I particularly appreciated the real life examples of what can go wrong with data collection and suggestions/best practices for how to handle that. It gave me a lot of ideas for how to deal with some uncertainties I was facing in some of my own research.

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.

Expected few more real life examples and hope to see some basics of Formal modelling. Found myself lacking in understanding the formal modelling concepts and how to arrive at the formulas.

Other than that the course helped me to get started in Data Science.

This is a good course, overall. Maybe providing more general examples related to the topics of the course makes this course much more useful and helpful for people who do not have any backgrounds of brain or neural systems in medical science like me.

Awesome course! the only negative thing is that all the examples are related to biostatistics. Examples related to other fields like economics, social science, psychology etc should have been included. Besides that it was a great experience

Brian makes a terrific job trying to explain in simple terms what a real life data science effort takes. Sometimes it was a little hard to understand because of how the instructor spoke but nothign hat a rewind and replay wouldn't fix.

Good overview of the reality of the challenges in data science. A glaring miss from my perspective was any real focus on the challenges of ML/AI based analysis. This module was really focused on traditional statistical modeling

I really enjoyed the comparison of what is ideal vs. what actually happens when it comes to data science. This was a very practical course and gave insight into what to expect from data science and analysis.

One more thing to add. The link to Study.com works. But Study.com wouldn't let me watch the whole video anyway; it requires registering and subscribing (after trial period is over). Not useful.

It was kind of hard to understand as I did not have any professional experience in data science. But, I am sure I can work in a professional environment now with the teachings of the professor.

Gives directions on how to deal with a situation where a clear conclusion may not be forthcoming from the analysis--- a situation that more often than not is likely to hold true in real world

This course is very interesting and worthwhile. we are living with data in our real life. good lectures. thanks to all team.

Dr DVNS MURTHY, DIRECTOR, BADRUKA COLLEGE, KACHIGUDA, HYDERABAD.

The course was very interesting and complete. The lectures were interesting as well. The reading material could be improved by adding more articles to reinforce the theory and examples.

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)

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.

Dr.Caffo is really well-versed with his field but I feel like concepts should be given more concrete examples so that they seem more interesting. Respect him all the way!

Examples used in this course are related to Lifescience and candidates like me find it difficult to correlate. It would be beneficial to use some common life examples.

Is good to have some data science background to enroll in this course, overall still good to learn and get the hint of how real life data scientist life is.

Good course - I'm now confident to oversee an end-to-end data science experiment. Some interactivity would make this the perfect overview of data science.

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

Many real life examples but in the courses the instructor introduced some new concepts which could be useful if get into more details of them.

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.

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

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