Excellent course materials, especially the videos, with content that is thoughtfully composed and carefully edited. Very good python training, great instructors, and overall great learning experience.
Great course to learn the basics! The supplementary material in Jupyter notebooks is extremely valuable. Really appreciate the PhD students who took the time to explain even the simplest of codes :)
By Partha S•
It's a wonderful course. Each and every part is well designed and very well explained. i
By vivek n•
Very helpful in understanding sampling stats...using python is like a cherry on top :)
By Mohammad S S•
This course is designed in the best manner you can ever approach to the data science.
By harsh s•
Just a tad slow for my pace, but the understanding and course material are on point.
By Shakshi M M•
Very good course if you are a beginner at learning python and data visualization
By Philippe B d A L•
This course is awesome. If week 4 have more practice, would be excelent!
By JIONG L•
Helped me understand some basic concepts of statistics, and insightful.
By Gabe M•
Could have used more python assignments or unfilled labs in week 4.
By Inti L•
Great Introduction Course to statistics concepts and python!
By Akshit A•
Assessments too easy. Course material was good though.
By lokesh k•
Very good starter course for statistics using python.
By Md. M H•
Pretty good to learn, have greatly enjoyed it!
By Felipe B•
Pretty interesting and well paced course.
By Gerard C•
Helpful introduction to the topic
By Mahmoud A H•
half of week 4 is almost a trash
By Joffre L V•
Great course, excellent!!!
By DHRUV D•
Very nice Course
By k k•
By aditi a•
By Liu M•
By Ata M•
By Elvan V•
Keep it up
By Mikel A•
In overall the course is good. However, there are some issues that could be improved, as for example:
- Using the NHANES database is come cases is not the most effective as you can spend some times trying to indetify or search for the variable they are asking for. Better instructions or the use of a simpler database could be an alternative.
- Some videos could be improved. There are compilation errors in the Python demostrative videos, in some other cases previoulsy not-explained functions are used (while similar functions already known by the alumn are available) or Python 2 functions are proposed (the course should be oriented to Python 3).
- I found that both parts of the course (stats and programming) are not always perfectly coordinated.
Despite these issues, the course is good and I will go to the next course with them.
By Maytat L•
Overall good but still have rooms to improve. I knew so little about statistics and Python. The concept is quite difficult but relatively new unlike other typical statistics courses offer. Practice assignments are very good but difficult. More guidance of Python libraries usage would help. Passing assignments were too easy. Strong foundations of using Python especially in libraries such as matplot, numpy, panda, seaborn would really help to better understand the concepts with a graphical presentation in Python. I would recommend this course for those who are familiar with those Python libraries already. For me, I need to learn more about those and would revisit the content here again to better grasp full understanding.
By Jaime A C V•
The topics that were seen in the course started in a very basic and understandable way but they evolved to much more advanced and difficult topics without a good explanation.Sometimes I felt no connection between theory and practice with Python. The large number of teachers does not allow continuity in learning and creates gaps.