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Вернуться к Introduction to Data Science in Python

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

Оценки: 24,685
Рецензии: 5,538

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

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

15 мар. 2018 г.

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 .

Фильтр по:

4301–4325 из 5,483 отзывов о курсе Introduction to Data Science in Python

автор: Antoine W

16 февр. 2020 г.

Learned a lot, but you constantly have to fight against the autograder

автор: Rajib M

9 окт. 2019 г.

Course content is good but the explanations need to be more elaborate.

автор: Sushma R

24 сент. 2019 г.

Feel too difficult to finish the tasks as they are little complicated.

автор: syed h

24 июля 2019 г.

Good Course but need to improve in conceptual explanations and visuals

автор: Carl W

14 янв. 2019 г.

I like the use of the Jupyter notebook. Don't have to wait for grades.

автор: Iván C S R

9 окт. 2018 г.

Good course to start understanding the usage of Pandas in Data Science

автор: Pragya A

6 авг. 2018 г.

good...but it could be more order to better explaination.

автор: 倪睿阳

1 июля 2018 г.

Helped me acquaint with Python and Basic Data manipulating techniques!

автор: Jarrett C

20 нояб. 2016 г.

This course is a challenging (and solid) introduction to using python.

автор: Guilherme M S F

28 сент. 2021 г.

T​he only thing I suggest is to change the assigments to be more easy

автор: Debasish C

14 июня 2020 г.

This course is very helpful to the introduction of data science world

автор: Shiv K K

28 дек. 2017 г.

Was extremely difficult to get the responses to all the assignments!!

автор: Ishita A

24 апр. 2020 г.

A little difficult for a beginner to follow but the course was good.

автор: Jagrut N S

18 янв. 2020 г.

It's really highly detailed and very good course for Data Scientist.

автор: Usman A

7 апр. 2019 г.

brilliantly maintained and organized courses , but not for beginners

автор: Deleted A

27 июня 2018 г.

A good python intro to familiarize with basic data science packages.

автор: Kartik S

6 июня 2018 г.

Outstanding course to get a kick start in the field of Data Science.

автор: Chinmay P

22 дек. 2017 г.

Was a good course that touched up most of the basic python concepts.

автор: CHAKSHU G

18 янв. 2017 г.

Finding optimal solutions for the assignments would have helped more

автор: Laura V T T

16 мая 2021 г.

Great introductory course, easy to follow and challenging exercises


3 февр. 2021 г.

I think some feedback on assignments would be helpful for progress.

автор: yotam h

22 мар. 2020 г.

great course! highly recommended if you like struggling by yourself

автор: nitin R

19 мар. 2020 г.

Course content is really good but can be explained in a better way.

автор: Vishen M

18 окт. 2017 г.

Really enjoyed. Assignments take a lot of time, but you learn alot.

автор: Ariana S C

17 авг. 2017 г.

Assignments need to provide better feedback when there is an error