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Opiniones y comentarios de aprendices correspondientes a Introduction to Data Science in Python por parte de Universidad de Míchigan

4.5
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25,766 calificaciones
5,734 reseña

Acerca del Curso

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Principales reseñas

YY

28 de sep. de 2021

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

PK

9 de may. de 2020

The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans

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5101 - 5125 de 5,685 revisiones para Introduction to Data Science in Python

por Taras P

10 de dic. de 2016

Top free course about Data Science. But I think lectures must be more detailed and related to assignments. And assignments could be less ambiguous and more clear.

por Manuela D

3 de ene. de 2018

Some exercises of the assignments where ways to difficult compared to what learned during lectures: much more details should be provided about data manipulation

por PRACHUR G

27 de abr. de 2020

the course is really good but there are issues with autograder. Though they are addressed in forums you'll have to go through them and hence wasting your time.

por Joshua C

24 de ene. de 2018

You'll spend more time struggling with the jupyter notebook (assignment platform) than actually writing or learning code. The lectures are really good, though.

por Yan X

4 de nov. de 2019

Great content. But some assignment questions are not that clear and might cost you more time than its worth. And feedback from mentor is not that responsive.

por Abhijit G

27 de abr. de 2018

The course is well designed and assignments are complex. What I did not like about this course is that the assignments are not well explained with examples.

por Narayan S

17 de ago. de 2020

The main problem is with the auto grader. There are too many issues making it cumbersome to get the assignment submission right in one go. Please fix this.

por Parth M

12 de jul. de 2020

Had to learn most of it by myself. Got discouraging at a certain point. Should have informed about the prerequisites.

Learn Numpy, Pandas before enrolling.

por Ryan T

18 de may. de 2020

Some parts were quickly rushed through and poorly explained. However, they did explain the bare bones of pandas, which was the main reason for this course.

por Pengyue S

1 de jul. de 2018

There is one critical technical problem lying in the assignment three and already caused hundreds of students' grade blank in the forum, including myself.

por Nehal c

3 de jul. de 2019

As a beginner I found it a bit of a brisk over the topic. There was a lack of basic questions. But in the end I was coping up and then the course ended.

por KUSHAL B

14 de jul. de 2020

too fast in explaining it was bit difficult to keep up with the explanation,small code example were taught but assignments questions was too difficult

por Aram M

25 de may. de 2018

Great course material, but the autograder system was frustrating to work with for assignments, and often made me less motivated to work on the course.

por Himansu A

16 de ene. de 2019

The course is okay for beginners as it is having only few lecturers for basics. Coursera experience was good. Overall i am satisfied with the course.

por Yaseen H

24 de sep. de 2018

The assignments are not even close what is being taught. We are taking this course so we get everything in one place. Curriculum has to be improved

por Alvaro B F

30 de ago. de 2021

I​ think the lecture about grouping could be improved with more practical examples, I had to search for external sources to understand the concept.

por Souvik B

8 de jun. de 2020

Not at all for beginnners. Fast-paced with more focus on self-learning and grinding,rather than focussing more upon the concepts. Dry presentation.

por Konstantin K

4 de mar. de 2018

Quite bad knowledge delivery from lectures. The course is rather self learning than course. A lot of vague points and uncertainties in assignments.

por VARUN K

4 de mar. de 2017

The course instructor could have been more elaborate with the examples. I felt there was a wide gap between the exercises and the course material.

por Justin L

6 de dic. de 2016

Assignments are challenging, but some questions are very vague and require lots of trial and error guesswork to get the autograder to accept them.

por pouya S

29 de jun. de 2018

Assignments are great to reinforce your learning. But the instructor does not cover many topics and leave you with a lot of questions unanswered.

por Hanwen L

15 de ago. de 2019

Please update the auto-grader such that is it compatible with current version of Jupyter notebook, very frustrating dealing compatibility issues

por Hemanta B

13 de ago. de 2019

This course is a nicely organized. However assignments are not completely clear. Especially assignment 4 needs more explanation and details.

por Joel B

1 de ago. de 2019

Subject matter was very good. Some of the assignments were not clear on instruction, and some of the Coursera functions were buggy or broken

por Paul A

5 de nov. de 2018

Material delivered a bit too rapidly to effectively assimilate. Often, further external research is needed to find solutions to assignments.