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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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24,725 calificaciones
5,544 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

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

SI
15 de mar. de 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

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5326 - 5350 de 5,489 revisiones para Introduction to Data Science in Python

por sparsh d

2 de may. de 2020

Instructor hardly teaches anything and gives you the toughest assignments to do.

por Taninwat W

14 de ago. de 2021

Need more exercise section to cement what I have just learned in each video.

por Scott L

16 de abr. de 2020

Pointless course. They teach you very little. Google is your actual teacher.

por Ridhi G

2 de feb. de 2018

the level taught in the course did not match the level of given assignments.

por Alakesh B

9 de jun. de 2020

Lectures were not clear and too short. A lot of external study is required

por Cunyuan Z

9 de jul. de 2019

Lectures are useless. But the assignments CAN BE pretty good practices

por Jair G

13 de ene. de 2018

I felt lost using Python as a data analysis software with this course.

por pouya g

1 de jul. de 2019

the corrector system was very bad and i m not undrestod my mistake

por Hussain

1 de may. de 2020

Very fewer video lectures and I felt Assignments to be very hard

por Rishi B

22 de jul. de 2018

I found the teacher boring, but his teaching was a little fast.

por Akansha

1 de jun. de 2020

for an introduction course it was just too much to understand.

por Nishant B

13 de jun. de 2018

Very fast paced and concepts explanation was not upto the mark

por OdmaaByambasuren

5 de nov. de 2020

Too general. I was expecting more to learn from this course.

por shailja

1 de jun. de 2020

very tough tutorial is easy but assignment are very tough.

por Satyam c

25 de may. de 2020

assignments are tough. didn't expect too much high level.

por Shivani P

9 de jul. de 2019

The lectures were not enough for the assignments provided

por Alejandro P A

22 de dic. de 2017

Good content but too fast pace and confusing assigments.

por Camilo E A P

27 de ago. de 2019

Jupyter notebook for assignments do not work properly.

por Sayali B

20 de jun. de 2018

The questions are very hard and not covered in training

por Deepalakshmi K

23 de may. de 2019

Dint teach anything used in the assignments properly

por Joao V O C d B

27 de jul. de 2020

The problem is the lack of practical exercises

por Christalin D

21 de jun. de 2020

It's asking for money to continue the course

por Hari S S

30 de jul. de 2020

A bit more motivation needed in this course

por W N

27 de nov. de 2016

Good material, let down by instructors.

por laxmi n r j

3 de sep. de 2017

Its too fast paced and less elaborated