27 de ago de 2016
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.
9 de set de 2017
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.
por Pavan M•
9 de nov de 2018
This course is very basic and completely theoretical. The grading of questions is not proper. The passing mark is 80% but there are only 4 questions. Answering 3 questions correctly gives you 75% and answering 4 questions gives you 100%, then where is the passing mark question.
But the content is good.
por Aydin A•
3 de jun de 2016
Was expecting more of the how to's and a bit of programming or at least concepts of the programming/statistics, but I guess there are different interpretations of the idea of a crash course.
Definitely geared for people who work with data scientists but not in the data science field.
por Sarge S•
11 de fev de 2017
Brian Caffo's lectures were rambling and confusing, with excessive use of jargon without proper explanation. His graphs were overwhelming with information, and little effort was made to explain the graph. Otherwise, the other lectures were very good, concise, and clear. Thank you.
por Edward W•
26 de set de 2015
A good introductory overview of data science. Grounds you on what you can & cannot do with data science. I find defining the question really impactful. Teachers were enthusiastic and the brevity of the course gives it good appeal for beginners who want to "get their feet wet".
por Elizabeth R•
27 de jan de 2016
Good, simple, straightforward, and applied. It starts to introduce you to the language and platforms of data science, but it is most definitely not a standalone course if you want to be conversant in the field. Really just a "taster" to get you into the specialization.
por Cecilia B•
8 de nov de 2017
More lectures but each lecture should be shorter. More examples for each topic would be good.
However it is a crash course, so it is more of an overall description of Data Science, which also gives you suggestions to enhance your knowledge in other courses
por Achal J•
11 de mai de 2020
This course is pretty basic so don't expect much. Basically this course is more reading than understanding but the articles suggested are good. If you are serious regarding data science then this course may be of not much use to you.
por Saurabh G•
12 de ago de 2019
Not all lectures in the course are well done. The one on the data scientist toolbox is good and could have more details. The one separating data science from statistics is too confusing. May need to redo the video on that one.
por Evgeny K•
25 de set de 2016
This course leaves you frustrated, as valuable information is only ad the end and at the beginning. It doesn't really answer questions of what are data science, big data, machine learning, how they interact and how to use them.
por Magne G•
19 de set de 2019
Okay content, very mix of level of information. Could state better the terms used in the DS world. The quiz part is not well formed questions, more there to mislead than actuelly verify the knowledge
por Girish R•
29 de out de 2020
The course material was good and the presentation was clear, however the Quizzes were very frustrating to figure out when I got them wrong. I could not clearly tell why the answers were incorrect.
por Daniel W•
15 de abr de 2018
I am trying to work out whether or not to get into data science, I thought this would help but still undecided.
I liked the grounding of principles, tools and methods required for the discipline.
por Francisco P S•
29 de mar de 2017
The course can use more visuals instead of videos of the face of the instructor. It can also use more interactive examples as this is a more executive view instead of having scholar examples.
por Enrique G•
29 de jul de 2020
Was actually expecting more.
Some of the lectures seemed just to theoretical and distant.
Several of the linked resources do not exist anymore or are accessible only with paid subscriptions.
por Peter P•
19 de mar de 2016
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•
10 de out de 2015
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•
18 de jun de 2017
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•
19 de ago de 2017
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•
28 de jul de 2020
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•
5 de mar de 2019
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•
11 de out de 2018
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•
16 de nov de 2015
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•
12 de jul de 2018
Pretty high level and quick. Hoping the remaining courses in the specialization give more depth. (Completed this course in an afternoon.)
por Yuhua N•
9 de mar de 2016
Lectures were fairly straightforward but not really that exciting and the lecturers sometimes felt a little unprepared or underwhelming.