學生對 IBM 提供的 什么是数据科学？ 的評價和反饋

I suggest that Coursera update the tutorial on how to use IBM Watson. I found that Coursera's instructions failed to match the current version of Watson that I saw. I tried several times to upload the images and run the program, but without any success.

It's an alright course going over basic terminology though for the two hours it took to complete, I don't feel like I learned that much content. Hoping courses 2 to 9 are a bit harder and more informative in the IBM Professional Data Science Certificate.

Decent introduction to the field. This could be a much much shorter course. The exam questions are tedious and based on precise recitation of exact facts from the specific articles presented, they not correspond to broader comprehension of the material.

This is a general introduction, probably a lot could of it could be reduced.

You will learn interesting things in the interviews (they are great).

But some videos are too broad ("blablabla") and skipable.

My advice : read the transcript and race for it

It is pretty basic. The quizzes aren't so relevant all the time. Perhaps it does not involve much difficulty because it is meant for everyone, no matter from which field of work. The videos are nice though and worth watching for general knowledge.

I recognize the course is introductory but even so it's very easy to pass (why bother to give assessments and grade if the bar is not set at a challenging level), the course material could simply be expected reading for a more advanced course.

A really good introductory course--has interested me to continue with the the "IBM Certification Certificate". Highly recommend this course for people who have an interest to get into Data Science and want to get a sense what it is all about.

Some answers assessed come from places either not clearly mentioned or absent from the course material. However, the course is a great introduction to data science and the many applications, I look forward to completing the full certificate.

I think its really Unnecessary course. Personally I want to study data science as fast as I can, and I felt unproductive and wasting-time when I studied this course. This course should be studied at the end of data science as a conclusion

Relatively basic introduction - course material assignments felt they more rewarded recital about an author's perspective than an objective review of many perspectives. Reading material was quite light. Fine to start with though.

Decent introduction to data science through video interviews of experts.

The assignements and quizzes do not reallly test your understanding of the subject but more your ability to remember details about a video yo've seen 10mn ago.

This course explains what data science is and what a data scientist is like. It also tries to motivate you by looking at job opportunities. But a whole 3-week course is a little bit too much. I completed it in under 4 hours.

Many videos with a lot of interviews that don't really add value. The readings are somewhat interesting. The course does not scientifically explain data science, but gives a broader view of the career aspect of data science.

I think this course is only a timid explanation of what a Data Scientist student needs to learn and ithe deal personal conditions before studying Data Science. It felt more like a sellers pitch than interesting information.

Very basic. I was hoping it gets into actual data science, but it spends most of the time explaining how to write academic papers and only one task that actually uses the IBM portal for machine learning. Disappointing.

Although the introductory videos are fairly good, the quizzes don't really assist with learning or demonstrate understanding of the material. Instead, they function as simple regurgitation of points from the readings.

Information was a decent introduction to Data Science for complete beginners. But, this information could have easily been condensed into one week of a more interesting, hands-on course in data science tools/methods.

The course felt like about 40 percent information and 60 percent promotion. Materials were of a mediocre level. Perhaps appropriate for the completely uninitiated but not useful for practitioners looking to level up.

While a nice introduction to the history, I would have liked a more thorough review or citations of the seminal work in the field, of the statistical methods used, and of the code used to generate machine learning.

The final exam and some quiz questions did not have answers that lined up with the assigned readings. They were nuanced questions with very particular answers that did not correlate to the knowledge of the course.

I could see there is more of reading rather of teaching. It would be better if the reading is reduced. Especially for quizes it is meant to read only last sections. But a quiz should cover all the topics taught

This course is a bit long and high-level for the length of the course. It should go a level deeper into actually running through an example of a Data Science focused case study or problem that is instructor led.

Quizzes didn't really test for knowledge, just hyper specific questions about a video or reading. Felt like just another way to enforce honor code to ensure reading rather than understanding or comprehension.

This Course could have been shorter. Many points seem repetitive. A few questions in the course were specific to those case studies which seems not quite useful to be asked in the Short tests in between.

Very generic information, which is somewhat useless. A lot of time is devoted to students talking about the data science and I don't think people taking this course would be extremely interested in that.