学生对 IBM 提供的 什么是数据科学？ 的评价和反馈

Very basic course, to be honest. The grading seemed to be dependent on memorizing exact quotes from videos. Looking forward to some of the more advanced courses in this series.

Too much introduction. There is no need to spend so much time on it. People that take this course usually understand what is data science. they need to learn real knowledge, not spend the whole week on introduction.

Videos often have disjointed or unrelated elements. Final week quizzes and mid-video questions often have useless or otherwise unhelpful reading questions. An example from week three's final quiz, "True or False: The Untied States Economic Forecast is a publication by McKinsey University Press." The answer is false and is covered in the reading, but the question has absolutely nothing to do with data science.

Too basic.

If you live under a rock and have never heard of Data Science, a Data Scientist or any terms related to this industry then this is a wonderful course for you.

For everyone else, it is a total waste of time.

This was a good introductory course, especially as someone with basically zero experience in the field. I've been struggling with where to begin (should I take a course on Python? R? What languages are even useful? WTF is cloud computing?) And this course gave me a good starting off point. That said, it wasn't technical AT ALL. It's really just a bunch of "fireside chats" with data scientists, talking about the languages they use, what concepts they're used for, what knowledge is necessary and what isn't, etc. If you're looking for a "roadmap" to continue learning on Coursera, this is it.

This is exactly what I feel the college experience gives students that online or self-taught learning lacks: context. AKA there are a billion courses on Python on Coursera, but none explain WHY I'm learning Python. This course does that. I'd recommend this course for anyone looking to start with data science from zero.

Very learning experience, I am a beginner in DS, but the instructors in this course simplified the contents that made me I could easily understand, tools and materials were very helpful to start with.

Very, very basic... completely useless and a waste of time. I feel like the only purpose of this course is to drag out the certification process so that it costs you more money...

Excellent quality content! It's a great introductory course that really gets you interested in Data Science. I would highly recommend it to anyone curious in learning about what Data Science is about.

I thought this course introduced the topic of data science very well. I think I have a much better idea how to describe data science and common terms associated with the field (like machine learning).

This course is not consistent with someone who would sign up for an entire certificate. This course is more suitable as a recruitment tool for a certificate program. Watching these videos was an absolute waste of my time.

Should this even be a course? Like they just say things that anyone can find the first thing on google if search you data science.

Poor course overall, not much "meat". An introduction to the subject that could have been given in one hour of lessons.

useless, wasting time

The course seems poorly pieced together with videos from Big Data University - which is now known as Cognitive Class. There is mainly little coherence into what the course is trying to teach in all the videos. Readings were given on a rather low resolution image file - that makes it difficult to read and kinda 1990s feel. Is it that difficult to save the pdf in text or include a higher res image file?

Similar to the point that a data science report should indicate the details and affiliations of the person writing the report, many speakers in the videos apart from the two professors does not have any background information. Who are they? Where are they from? What background are they speaking from? All these are important context for learning.

I did learn something from the final assignment though. However, that was personal reflection and learning from peers. Thinking whether I should continue with this course.

Waste of time. Most of the material was "fluff" about data science. What was actually useful could have been accomplished with a 2-3 page pdf. Only finished it, because I'm taking it as part of the IBM specialization through my work. I REALLY hope the other courses are more useful and worth the time. Very disappointed in this course.

Very learning experience, I am a beginner in DS, but the instructors in this course simplified the contents that made me I could easily understand, tools and materials were very helpful to start with.

A very basic and shallow introduction to data science. Too much hand-holding and too much time spent discussions of little value. Ideal for someone who is very young and very new to the field., everyone else should avoid it.

This cannot be considered as a course it tells some general info about the experience of some professors but nothing technical, of course it's useful but it's not really worth it

The course doesn't teaches anything except for explaining data science benefits and examples.

I throughly enjoyed the course and the fact that everything was explained thoroughly. I always enjoyed Dr. White's personal experience with Data Science as well as other Data Scientists point of view.

Very nice course and it has a piece of very nice information taught by professionals. The content is related to the practical application of concepts which increase interest in you to proceed further

Good for fundamental knowledge of data science and data scientists.

It is also inspiring for young people like me to get ready to step into the world of data science.

Great course

Friendly and gentle introduction to data science! Can't wait to go further...

I liked this course very much. The way it is organised to collect different data scientists opinions about the same topic, make it very valuable to the ones who are starting the road to Data Science.

Good overview of data science, its history, and uses of data science.