創建者 Carl W•
Apr 27, 2019
The course is easy to follow, well organized, and assumes very little background. It effectively demonstrates the power of Python in large data applications and provides insights and guidance on which tools are best used.
創建者 Cambron T D•
May 22, 2019
Great first class in this series.
創建者 Zakir U S•
Jun 24, 2019
Over all a great course for beginner
創建者 Mohd Z A•
Jun 30, 2019
Excellent to start your career in machine learning!!!
創建者 Oriol P M•
Aug 12, 2019
Excellent and interesting course
創建者 Sebastian S•
Jun 22, 2019
The positives: I liked the design of the final project, and how users were encouraged to 'get out there' and find some interesting open source data sets. The lectures were well structured with good narratives and good examples.
The negatives: I would have liked a bit more focus on actual visualization libraries like matplotlib and maybe seaborn. When covering the data types (date, string, boolean etc.), it might be worth adding an extra week or so were these things are done with the help of the standard library pandas. I feel like this is what people will end up doing anyway bc there are so little alternatives in python to do processing, so a course on data processing should ideally cover that library.
創建者 Jonas J T•
Aug 23, 2019
Quick intro to data processing. More material on numpy and pandas would have been nice. Im still trying to figure out why the specialization mentions "Design Thinking". At least in this course...not a single design thinking concept was mentioned.
創建者 Davide C•
Jun 18, 2019
The test scripts make no sense.
創建者 Paul E J•
Jul 03, 2019
This is not a Python introduction, but the authors approach it as if it were. Even the most basic data scientist will not calculate averages in the way described here. We'd use pandas or similar to get not just means, but other summary stats as well. For a Python course, I could understand doing it the way shown here. But not for data science.