學生對 IBM 提供的 什么是数据科学？ 的評價和反饋

It does well to introduce the student to different areas of data science, applications and industries. To improve it, would love if more introductory terms are used and role clarity are explained a little better.

What tools and technologies and courses to pursue.

Many of the test /quiz questions are based on memorizing relatively useless things as a data scientist. The checking of understanding the concepts can be done a lot better than 'who said what' and 'who used what adjective', and 'who worked for which company'.

The course is great, but it is a bit difficult to navigate through coursera. Additing in small bits to manage the coursera portion would be great. Also, the course was designed 3 years ago, so i am a bit concerned about how up to date this information is.

The course does not emphasis on data scientist needs to have an understanding of research methodology in some cases. Data scientist needs to understand the needs of their clients and what questions to be answered before start pulling data out to analyze.

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

T​his didn't feel like a very substantive module. I'm going to feel like an imposter if the rest of the modules are as lightweight. The forray into IBM's Cloud/Watson was unsettlingly superficial. Surely we will go deeper, right?

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.