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Отзывы учащихся о курсе Introduction to Data Science in Python от партнера Мичиганский университет

4.5
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Оценки: 24,856
Рецензии: 5,563

О курсе

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....

Лучшие рецензии

YY
28 сент. 2021 г.

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 мая 2020 г.

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

Фильтр по:

5126–5150 из 5,507 отзывов о курсе Introduction to Data Science in Python

автор: Chen L

5 апр. 2017 г.

More programming details should be included.

автор: Pravin A J D

9 дек. 2018 г.

can be made a bit detailed course on Python

автор: Maxim P

14 июля 2018 г.

less talking more usefull guiding is needed

автор: Rohit R

12 июля 2020 г.

Lecture explanation could have been better

автор: Jinsuk H

15 окт. 2017 г.

Good materials but video doesn't help much

автор: Oleg K

4 нояб. 2018 г.

Compare to Machine Learning from Stanford

автор: Shraddha K

2 мар. 2019 г.

More elaborate lectures would help more!

автор: 丁浩然

7 окт. 2018 г.

The assignment is a little bit hard....

автор: COMP-25 N S P

15 июня 2020 г.

more practice video need to be added

автор: Pakin P

10 янв. 2020 г.

why not have expect output for check

автор: Venkata S K R C

5 дек. 2017 г.

Totally not for absolute beginners .

автор: 李得意

17 мая 2020 г.

Homework is too hard for beginners.

автор: SAHARSH G

2 нояб. 2019 г.

Should be little more descriptive.

автор: Sara R

23 июля 2018 г.

Please change your teacher. Thanks

автор: Murali

3 апр. 2018 г.

Explanation could have been better

автор: Gagandeep S

13 мая 2018 г.

Good course but not for beginners

автор: Tracy C

20 дек. 2016 г.

assignment is a little bit messy.

автор: Osman D

4 июня 2020 г.

The assignments were too vague.

автор: Samyak J

20 июля 2020 г.

The instructor is a bit fast.

автор: Keerthana V

24 июля 2020 г.

overall good introductory!!!

автор: Jahanvi A

22 авг. 2019 г.

The instructor went too fast

автор: PAVAN K

8 июня 2020 г.

But seems like its too fast

автор: TARUN K S

5 июня 2020 г.

awesome course and platform

автор: Dhanush P

5 апр. 2020 г.

IT was more than self study

автор: Carlos A V G

4 июня 2020 г.

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nts are very hard.