Ratings and Reviews for Introduction to Data Science in Python

i have gained so many skills from this course.

Overall nice and I was able to move at the right pace for me, which is pretty fast. I was annoyed by the many little mistakes, though, hence the low rating. More than 10% of the quiz questions had something wrong with them so that there was no one unambiguous right answer you could give. In a couple of cases you had to choose an answer that was clearly wrong to get the points for it. What made it worse is that given the high ratings and the number of students already enrolled I fully expected everything to be stellar. I reported all the errors I spotted to the discussion forums, but will not be bothering to do that in the future since the reports and trying to explain my cases proved in general more trouble than they were worth. Some things were promised to be fixed, some were ignored. So, mixed feelings and a mixed rating

I was really looking forward to this course. The lectures and the readings are great. I learned much there. I spent an inordinate amount of time on the homeworks, though. The problem formulation and grading were a fiasco. Even when the questions were stated clearly, you had to contend with hidden assertion tests, that offered very little in output describing how to correct your answer. Also, I checked my work always against the files in which we were supposed to perform our exercises. Assignment 3 was particularly atrocious; in that, the population sums the autograder expected could not be had, since the estimates were normalized differently in the actual file. Additionally, the quizzes were not well planned. Once, we were asked for the top 3 ranked individuals in a class (greater than 4), but the answer required by the autograder wanted fourth rank included; you received credit for answering incorrectly and were dinged for answering correctly. I pointed this out, but received no response.

I like the structure of the course and its content. I would like the assignments to show the values that we must achieve (or at least the beginning of the value), so that we can have idea and find our mistakes faster, I took double or triple time to do the assignments

Litt! for pandas and numpy. Quite engaging assignments which reinforce concepts taught in video lectures.

course content is too good and each assignment problem is conceptual which is very useful for me.

This course is was very challenging since I have to pretty much learn python on the fly and then understand the data science part of it

Hace falta abordar mas temas en las conferencias o mas ejemplos, es bueno buscar y explorar por uno mismo las capacidades de les herramientas pero en cada assigment es supremamente complicado, mas aun cuando la respuesta debe ser exactamente igual (sin redondear).

Get ready to load and cleanse data with Pandas. Also, great for experience with NumPy and a bit into SciPy at the end. Make sure to keep up with the assignments work!

Skill