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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: 24,558
Рецензии: 5,516

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:

4251–4275 из 5,462 отзывов о курсе Introduction to Data Science in Python

автор: Sameeksha K

6 авг. 2021 г.

There are more functions that can be explained in pandas & especially REGEX

автор: Animesh K

18 нояб. 2020 г.

Good course. Assignments are challenging. Overall good introductory course.

автор: Alonso G L

19 февр. 2020 г.

Great opportunity to learn pandas. Some previous experience is an advantage

автор: Anindita N

23 сент. 2018 г.

good but Statistical analysis part should be more explanatory with examples

автор: Matthew W

8 окт. 2017 г.

Contents are not hard but assignment need more practice and time to finish.

автор: Thibaut L

11 июля 2017 г.

interesting but could provide some mathematical background for further info

автор: Rajib K

12 февр. 2021 г.

I would prefer to have a generic assignments, this is too much US centric.

автор: Tarush B

14 июня 2020 г.

The focus was on self study and that was really a good learning experience

автор: Karan M

23 июня 2019 г.

Excellent course with lots to learn, but also loads of self learning to do

автор: Jesús P A

23 февр. 2017 г.

Perfect to get hands on with python programming for data science purposes.

автор: Niraj K

22 дек. 2016 г.

Great course, Gives good outline to navigate through the essential content

автор: yasmina D

17 июля 2020 г.

i wish we could have some practise assignements like in the other courses

автор: Anuj K

21 янв. 2020 г.

Coding environment should be improved. Assignments should be more guiding

автор: Anurag M

6 янв. 2020 г.

Assignments are really good but the pace of teaching can be improved upon

автор: Bernardo J

15 дек. 2017 г.

The assignment materials in the 3rd and 4th week need a SERIOUS make-over

автор: Ng Y H

19 нояб. 2017 г.

The lecture python examples could be closer to the homework requirements.

автор: Kevin D

26 июля 2017 г.

Interesting course with pretty useful interactive programming assignments

автор: Jorge G

30 авг. 2021 г.

It covers necessary topics for my job purposes, but it's not sufficient.

автор: Karan K

1 мая 2020 г.

It was great experience learning the basics of data science with python.

автор: Daniel M

18 нояб. 2019 г.

Very clear and straight to the point, yet a bit advanced for a beginner.

автор: dibyaranjan s

11 окт. 2019 г.

assignments are a bit tough, some of them are advanced than the teaching

автор: Dhara A

20 июля 2019 г.

it is really nice course which gives you complete basic of data analysis

автор: Deleted A

6 мар. 2019 г.

could have explained Hypothesis testing in better way with good examples

автор: AKI

30 янв. 2018 г.

great course!but some assignments lack of clear instruction or mistakes.

автор: Carolina F A

27 окт. 2017 г.

The course is pretty good. However, the tasks are no easy to understand.