Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!
This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)
par David N B•
Very little assistance from Moderators
par Tushar M•
the course content requires an update
par Deepratna A•
Could have made it more interesting
par Thomas M•
Not great quality of video content
par ABHIJEET B•
CHF case study was the worst part
par Ali M R H•
The case study was hard to follow
par Ramakrishna B•
More explanation would be great.
par Glenda m•
Falta mas ejemplos descriptivos
par sairam p•
concentrated largely on theory.
par Anup U•
it should be more descriptive
par usha y•
very nice course knowledgeble
par SANDHI J•
Should be more interactive
par Salvatore P•
too much simplicistic.
par Igor L•
Too basic and too easy
par Ar R H•
The journey was well
par José M P A•
A little boring...
par Richard B•
par George Z•
par Rohit G•
par Max W•
par Roxana C•
This course was fairly disappointing. Apart from the actual steps of the methodology, it does not properly teach the concepts mentioned in the course. For instance, the ROC curve used in the case study: I actually understood how it works from the forum, because one of the admins was kind and has given a very professional and well explained answer. I wouldn't say this course is a waste of time, but I believe it addresses superficially most concepts. I am a firm believer in explaining only a couple of things and doing them very well. The labs are bridging some gaps, so extra points for that. The chosen case study is not thoroughly explained - it uses methods that we are not given any context for and only the very obvious elements are explained. The parts addressing the case study need a serious revision. If you are not following the Data Science Specialization, I would recommend you find a better course on Data Science Methodology - this course is not it.
On the plus side, I did like the final assignment: yes, it is theoretical, yet it helps you really revise all that you've learned in the course.
par Stefano G•
Concepts are well explained. Case study is instead confusing and requires additional knowledge and experience (i.e.modelling section).
Sometimes topics are repeated in different sections making it difficult to understand if a task should be completed in a phase or in the next one (i.e. training sets are repeated in both data preparation and modelling).
Lab is not so useful, because it consists in executing python code without a complete understanding.
This course is fundamental to understand the methodology for data science, however I had to look at the videos multiple times to get an overview and I still feel I'm not familiar with it.
par Ivan B•
Not a useful course overall. The basic premise is fine and logical, but this course did not do a good job differentiating between the different steps involved in the Data Science Methodology and the terminology chosen and used was not explained very clearly or consistently.
Very dry and wordy videos. Example cases used were not straightforward and did not help me understand the concepts that were being conveyed. Good concepts to learn, but this course could have done a much better job at explaining them.
par Oleg N•
Thank you for the labs they were great!
Now about everything else:
1. The quality of videos was awfull: the sound was noticeably lower than in previous courses of the specialization,
2. Slides almost irrelevant to text material read, lots of material in such quickly-paced lectures,
3. Lots of medical and mathematical/statistical terms (and other advanced English vocabulary) make this course hard to comprehend to students who rather not that fluent in English.
par Maulik M•
Too much theory from the methodology being read out in the videos!!! Needs to be anecdotal and explained practically. The case study taken in the videos also could be simpler. Some concepts like modeling etc that needed to be focused on get the same focus as anything else. There is mention of predictive and descriptive across videos. But this could have been much better sequenced.
But the Jupyter notebooks provided a lot more value than the course itself.