The content was very good, but the assessments were subpar. Why does it matter if I remember who was quoted in a text as saying something about data science? How does that help me get a job as a data scientist? Too much of the graded work was based on insignificant parts of the readings rather than things that are helpful to know about data science. Plus the final assignment asked about 10 parts of a report which were never clearly defined in the reading (and actually there were 11 parts mentioned but somehow we were supposed to know which 10 they were asking about).

I found some information useful, and the sequence of modues is interesting. However I would invert the way the modules explain what is data science. I would place people giving their opinion in readings(instead of videos) and examples of applications of data science in readings in videos (which are much more interesting and kind of situate students on what data science is). The quiz is interesting, but I really didn´t like the question about the name of Google CFO. I think the overall target of this quiz have passed remembering names for tests a long time ago.

There were a few spots where the information in the labs did not match up with the actual site; I assume that they updated since the course was made. It was not hard to figure out. Additionally there were a number of videos that had problems with the transcription below. There were many that were about 3 lines ahead of the video and there were at least two that were for an entirely different video. I assume the videos were updated recently but the transcript was overlooked or something similar. Other than those minor troubles, I enjoyed the course.

Warning for those whose native language is NOT English:

These IBM Data Science courses are in DESPERATE need of review by a native English speaker. If English wasn't my first language, I can only imagine how much I would have struggled. To be fair, this particular course didn't contain anywhere near as many grammar, syntax, and audio transcription errors as some of the other courses in IBM's Data Science collection, but it is still pretty unbelievable that they expect us to pay money for courses that haven't been properly reviewed and proof-read.

Impressive contents and materials.

experienced facilitators from impressive backgrounds in data science and analytics.

I like the intermittent review questions, helps in maintaining focus.

Thank you for the introduction and access to the IBM Watson VR service, I love the hands on exercise, took some pictures from around the house and tested the VR, Impressive, and still growing. However, I feel IBM Watson VR can still improve in some areas of systemic biases, may be due to cultural gaps...

I will recommend this course for anyone interested.

I took this course as the first in the IBM Data Science certificate sequence. The content was good, but the certificate is billed as being for people new to data science and in much of this course the speakers suggest you should have a background in statistics and should have some programming experience to be a data scientist.

From what I can gather, I think the other courses in the certificate will prepare people even without those things in their background, but it did give me some concern about whether I'm mistaken about that.

Videos were thorough and concise, however I did not like that the transcript did not reflect everythign the speaker was saying in some parts and then in other parts had more articles (a, uh, the). To me this seems like a fix that can be completed during review. Additionally, it felt as though the rubric for the final assignment had more emphasis on specific words being added in a response than the concept or idea being realized throughout a students answer. Thanky you for your time and appreciate the introduction course.

So far the experience has been worth every penny. The quality of content disseminated by lecturers, videos is awesome. There are instances where we a real person to guide us would make the process even more smooth and faster, viz., logging into IBM web, installing watson assisstant to name a few.

And i would really like to come in contact with a real mentor, a data scientist who is an industry professional who can give an inspirational insight to boost morale and motivate us, he/she can be a convenor of the program.

This Data Science Course hassupported my confidence building as a Business Analyst. I was able to take actionable knowledge from the level of data, collated by different individuals and works of life. I see Programing as a underused , new avenues are opning and generating new growth for Research and Development in the health, marketing and research sectors. Learning pace is encouraging and easy to follow. Being exposed to likely earnings' of a Data Analyst is also a game Changer for me.

Than you.

Olatunji O

Overall the course was enjoyable and provided good information from relevant sources familiar with the course topic.

I'm sure you here this a lot, but the peer-reviewed grading assignment is not a good approach and would recommend that this feature be removed. I know Coursera has good intentions with this and they are trying to promote positive interaction engage learners to communicate with one another, but individuals taking these courses are not interested in the forum's for the most part.

This was a good introduction to Data Science, and what a data scientist should expect to do. It also included a good description of what type of background might be required along with educational requirements for someone looking to get into Data Science. The only reason I didn't give it 5 stars is they tried to sell it a little too hard. I'm already taking the course and have demonstrated my interest. I don't need to be sold on why being a Data Scientist might be something great to be.

Self paced and easy without being boring. Interesting material. I felt the peer reviewed assignments and quiz portions promoted rote memorization vice actual understanding. All the ones i grades were clearly copy paste form the reading, yet by the grading rubric, they all scored perfect. The section requiring an account creation and use of the Watson AI application was a waste of time, and its rather annoying to have to create yet another account among the hundreds of others everyone has.

The course is a very fast and high-level look at data science. I enjoyed it quite a bit and would recommend it to anyone who is nervous about exploring data science. The only reason it didn't get 5 stars is that it could use some updating. Some of the screens on assignments don't match the Watson platform, and Watson no longer allows you to use the free version to do the assignment requested. Had that been working, it would have been 5 stars for sure. Really worth taking.

The course was a great introduction to the world of Data Science. I whitnk it would be nice if, regarding the technical aspects of data science, you could include more tools or bibliographical references to train one-self in statistics, math and/or computational skills. Also, when it comes to definitions, there was some repetitive content along the course.

I am really grateful for having had the opportunity to learn about this passionate field. Thank you so much!

The course was rudimentary and not as technical as I was expecting, but did give a really good introduction to what data science actually is and what data scientists do. The articles were more helpful than the videos (though the videos were still worthwhile) and for me the most directly useful part of the course was learning how data scientists structure their reports and deliverables at the end of a project. Definitely worth your time if you're new to the field.

The course provided good foundation in explaining importance of data science, it's tools and skills and use, I felt it was rather content light, it spent a lot of time on justifying why, rather than how - I was hoping that in a 3 hour course, the techniques an skills would have been covered more in depth. I like the fact non-scientific skills such as curiosity, storry telling and enthusiasm were stressed and given equal importance as the technical ones.

I very much enjoyed the course and got a good overview of data science, I think. The combination of video, quiz, and reading was nice and allowed me to stay engaged. The only criticism is the varying quality of the provided literature (not the content, just the display - looked different every time and was difficult to read due to lack of quality) and room for improvement of the answer fields for the assignment. The layout had some issues.

The course is very well structured and the topics organized. All the explanation is straightfoward which makes a complicated subject seem easy. The only downside is that some questions made throughout the course were not very practical and sometimes focused on small details that are unimportant, such as "which Magazine said data science is the sexiest job?" instead of "Why data science is the sexiest job according to Magazine XYZ?".

A really useful and broad introduction to the data science world! I really enjoyed the organization of the course, as well as the speakers. The only reason because of I am not giving 5 stars is the reading section. Although all provided articles are useful, sometimes they contain some technical jargon not explained in the lessons (because it is an introductory course). Overall, an essential introduction to the specialization.

Very very detailed which is something I like. Only reason I didn't give it a full five stars is because the last quizzes in course 1 of this specialization were locked over a weekend. I'm guessing many factors in this decision were at play but I definitely am excited with what Coursera offers and was without Coursera for a sunny weekend. I'm hoping the rest of the courses in this specialization don't have any locked portions.

The content formed a great introduction to the subject but I felt that the quiz-format and peer-reviewed task could have been a little more challenging. I feel that the ease of the questions devalues the course somewhat. The questions should require understanding of the topic rather than purely 'copy from the text' style answers. But, I want to re-iterate that the content and quality of the information provided was excellent.

Generally good content. This is good for beginners with little or no background to Data Science. Some topics were a bit mixed up with each other; but all put together the content was good for a beginner's course.

It may be good to add some videos / content from real life corporate stories. Right now, with most of the videos being of academicians, the application of data science in corporate / business scenarios is not emerging

Great course for starting with the data science. I really liked the format of asking the real data scientists the questions about their work - their insights were very helpful.

Giving 4 out of 5 just because of the quizzes - they test some strange knowledge, like "in what company worked the person who said that thing". About 50% of the questions, including the final exam, are completely unrelated to the data science topic.

Excellent effort by whoever designed this course, however i think the course should include some real life case studies to better help understand the Scope of the field of data science. Or some real life examples like my instructor once told story about how Facebook and Walmart and some other business giants have used data science to reach success. it will kind of help motivate fresh graduates to move into this field.

First, I'd like to say thank you for providing me the opportunity to learn skills that feed my curiosity.

I'd like to point out that I failed to realize that one needed to share their final submission via a link, and post them in the discussion board. There may be more people after me that make the same mistake, so may I suggest adding an extra reminder/instruction regarding the means to complete the final submission.