This is a great starter course for data science. My learning assessment is usually how well I can teach it to someone else. I know I have a better understanding now, than I did when I started.
Is really hard to summarize the potential of Data Science and being clear, but I think that the instructors have done their best, so that we can achieve the most from the Course.\n\nGreat Job!
por Peter P•
Great course for somebody who does not know anything about data science. When doing this specialisation there should be credit for those that did the other data science specialisation
por Scott K•
Very basic course. If you know about data science, data analysis, or machine learning, you may find this class basic or boring. Good intro course for those who have no prior knowledge
por Sam B•
Interesting course but structure was a bit odd I thought, it was not clear why so much time was devoted at the outset to the difference between Machine Learning and data science.
por Yi P C•
not bad but not good enough for showing examples like data visualization and how to build the mind of data science for several fields (finance, marketing, sales and so on)
por Rajkumar S S•
I felt that the content of this course was too little. It should go one level deeper and explain the challenges that managers may face when handling data science projects.
por Leslie T•
The material and lectures are good but the quizes are not very helpful and somewhat random (in answers). The small number of questions make them very unforgiving.
por Raymond T W•
A bit too lengthy for the points to be learnt. Can get more done in less time and fuss. Too many examples especially if one wishes to cover 100% of the material.
por Marco C•
Good course, with general and not over-detailed explanations of all the relevant topics in data Science. A good, general overview definitively worth working on.
por Jason M•
Pretty high level and quick. Hoping the remaining courses in the specialization give more depth. (Completed this course in an afternoon.)
por Yuhua N•
Lectures were fairly straightforward but not really that exciting and the lecturers sometimes felt a little unprepared or underwhelming.
por Jochen H•
Interesting course and good learning. However for me some of the video lectures were a little bit unstructured and difficult to follow.
por Robert Z•
The quality of audio wasn't amazing. Get yourselves better mikes, guys. The language was not properly graded for the beginner's level.
por Yousuf A•
A lot of the topic is described in a difficult way using unknown words(for a beginner) and with examples that I did not understand.
por Dave W•
Pretty basic course. Good if you are completely new to the space. There are good references to tools for further investigation.
por Stephanie M D•
Nice overview for those of us unschooled in the language. Syntax of the notes and text is in need of major editing-proofreading.
por AKASH S•
the course must be more explanatory and the professors should not speak so fast. let us understand things. It takes time.
por Wenni Z•
Very preliminary, most of the course don't have a PPT or handout. May be helpful if you know very few about data science.
por Hugo J•
It's a nice to starting course, thanks for the effort on developing and keep updating with new cases, tools and info.
por Pablo T•
ok introduction if you have no background in DS.
if you have experience, take the quizes first, its pretty basic.
por Deleted A•
Would have been better if quiz access is available for free so that it is easier to reinforce concepts learnt.
por Daniel S•
I know its a crash course, but probably need to be less general management stuff and more on data science
por Karthik S N•
Really basic course. Not needed for people you have already done data science specialization in coursera
por Aarti K•
The teachers spoke really fast with which it became difficult to grasp the words. Overall it was good.
por Hason G•
Would have liked to seen more examples from other industries for those not in health industry
por Peter L•
Added value is highly dependent of your experience with data analysis or data engeneering