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.
Terrific introduction to the Data Science course. Never expected but was extremely excited with the quality of content, speakers and a very honest attempt to making this course interesting.\n\nKrishna
By Tirthankar B•
Very high level view of dat scien
By Axel B•
Actually not much happening here.
By Satya S•
A lot of unnecessary information
By Mark H•
Pretty basic. Didn't learn much.
By Joseph S•
I didn't think it was helpful.
By Deleted A•
Very boring.Not useful at all
By Nicholas J•
It's really not very useful.
By Shivam D•
A very very basic course...
By Sean M•
very basic introductions.
By Brandon M•
Correlation = causation
By Chaojie L•
Maybe shorter is bet
wordy, wasting time
By Michel M E•
Not useful at all.
By Shubangini N•
It was very basic.
By Felipe S•
Very poor content.
By Alpana T•
It's too basic.
By Rushan N•
Way too easy
By VINAY C•
By Syed A A A•
By Manu k•
By Julian W•
Really disappointed with the whole specialisation... I am leaving this review here because probably you might not check the others courses before you start it.
Specialisation is short and it is the only good thing about it. It took me I think 10-12 hours to do it.
So first of all the whole thing is not really informative. A lack of videos - Most of the time there is only "power-point"presentation with code written on it. I don't really understand why they have narrator who just read text - no emotions almost like a machine.
1. You will spend a lot of time learning listening to videos about how sexy is to be data scientist... and that parents start sending their daughters for data science (sic!), and that it is a new science... Plus some rather simple information which you rather know taking into consideration you want to study it online. At least it is nice to watch - there is life in it.
2. You will spend the whole course watching different notebooks like jupyter R studio etc . without really learning any useful stuff. In the end you will just click run to create some already written commands in python. Yeap that's it. I know it is intro but adding 1 +1 third time in different console...
3. You will learn some methodology - A lot of complicated knowledge read by narrator who is not making it easier or more interesting. Almost like somebody reading you technical book...
4. SQL - you will try to learn it from presentations. I think there are no proper videos just images in narrated power point presentation. I watched some coursera lectures about sql before but still I had problems with following it. To make it worst you will have to use IBM products which are FREE - other reviews are probably outdated. The problem is that materials from this course are also outdated. So they are presenting you IBM tool-set which is already different. It is a problem because they are not even trying to show how they work just where to click.
I managed, you will too but, IBM, please do better.
By Hakki K•
I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".
Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)
Course 1: approximately 9 hours to complete
Course 2: approximately 16 hours to complete
Course 3: approximately 9 hours to complete
Course 4: approximately 22 hours to complete
Course 5: approximately 14 hours to complete
Course 6: approximately 16 hours to complete
Course 7: approximately 16 hours to complete
Course 8: approximately 20 hours to complete
Course 9: approximately 47 hours to complete
This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.
By Laurentiu-Lucian A•
The course content is exciting and high level. In this course the student does not do any hands on data science, except the occasional introduction to an IBM tool. Instead, they are introduced to a broad range of topic, tools, and perspectives on data science. It is a good introduction to the subject, and I would likely have given this course three stars, maybe four, had there not been so many large bugs, that at the time of this writing, almost two weeks since posting in the Discussion Forums and contacting Coursera Help several times, has not been fixed.
For anyone going into the course, please take screenshots of all quizzes and assignments you complete. If you experience the same issue I have, and hundreds of others are having, than your progress data may get erased. I should have received my badge for completing this course two weeks ago but it is still saying I have "overdue" items and that I've completed everything at the same time.
I am sad to give this one start rating, but so it goes. I hope they fix this as soon as possible, and it may end up affecting people's billing.
By Svyatoslav A•
Has too rigid an understanding of a complicated field. The track would be better off without this class, as it's just confusing. Videos of "real people talking" are a big waste of time. Videos and material contradict themselves multiple times. Quizzes test memorization, and not actual understanding of the material (as in, only ST types will do well on MBTI typology spectrum, but SF, NF, NT that have better understanding will achieve worse grades, at least give challenging questions that apply knowledge learned, not just ask people to define terminology), peers literally copy paste answers for the final exam portion. Basically, just horrible and a waste of time all around, so at least make it just one hour.
Final project being in academic format is the worst, as data science projects in the real world are usually in the form of dashboards, presentations, or products... so this academia bs is literally useless in preparing people.