The entire explanation of each topic is good but it is too fast. There should be more number of examples for each topic and for various cases. Other than that, It was very beneficiary for me. Thank you!!
Ratings and Reviews for Introduction to Data Science in Python
Back to course Page
Reviews and Ratings
Reviews
good
Los ejercicios son muy dificiles y hay que hacer mucho reaserch en los foros para lograr llegar al resultado. Las pruebas son diagramadas de tal forma que a veces es dificil llegar por errores pavos al minimo resultado esperable para aprobar los assignments (ej run_ttest)
A bit complicated grading system & Jupiter itself if you prepare assignments offline.
A lot of information and definitely need more than 4 week(6-8h) to accomplish.
The final tests are problematic in the evaluating phase
The assignments given were too difficult. Students have to spend a lot of time doing self-study and using stackoverflow. Providing basic practices for students would be much more helpful for them to tackle difficult questions.
Topics covered are interesting as next steps when you have some basic programming skills in Python. However, the introduction and explanation of new concepts feel very rushed; a one minute video on map(), then lambda with a quick exercise without further explanation, followed by list comprehension at the same pace. I often found myself stopping the videos and googling for further explanation to understand what is really going on. If instructors feel that such concepts should be familiar to someone participating in the course, then I'd recommend not covering them at all, rather than rapidly rushing through.
Excellent course!! Covers the basic concept of Statistics with Python.
The topics could have been explained in little details, however the exercise were quite challenging
