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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: 26,495

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


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.

Фильтр по:

4626–4650 из 5,808 отзывов о курсе Introduction to Data Science in Python

автор: Abir H R

10 мая 2020 г.

videos should be a more informative and Very hard exercise

автор: Haven X

3 мая 2020 г.

good but the online notebook version is a little bit older

автор: Mike B

11 окт. 2017 г.

Good, basic introduction to basics of the Python language.

автор: Ho Y C

12 июня 2017 г.

The exercises are good for thinking and learning of python

автор: David A D A

4 сент. 2020 г.

It was a little hard for me but i learned a lot.Thank you

автор: NIMIT T

26 мая 2020 г.

it was great to learn this whole experiance is amazing: )

автор: Harshit Y

10 мая 2020 г.

Assignment level is quite high as compared to content tau

автор: Nikhil Y

13 дек. 2018 г.

Thank you Coursera for providing such a wonderful course.

автор: Christopher R J

24 авг. 2018 г.

It is a best introduction about python and analysis data.

автор: Harmandeep K

31 мая 2018 г.

Should make assignments more like a real business problem

автор: Ricardo W B

1 окт. 2017 г.

Some of the assignments require too much time to complete

автор: Amit m

15 мая 2017 г.

Good introduction. Hoping to see an intermediate course.

автор: Diego M

22 июля 2020 г.

Very meaningful information and challenging assignments.

автор: Nikhil J

17 июля 2020 г.

one of the best course to get started with data science.

автор: Christopher O

10 июня 2020 г.

It was quite great with plenty of datasets to play with.

автор: Shikhar S

2 сент. 2019 г.

Quite good, i wished they included more pandas functions

автор: Thiébaut L

15 мая 2018 г.

A good start to learn about data management with python.

автор: Chuying Z

24 дек. 2017 г.

A great course to experience data science through Python

автор: Amrita A

10 окт. 2017 г.

Fast paced course but still useful if you are getting yo

автор: Jinbin F

7 мая 2017 г.

It is a good course, but a little difficult for a newer.

автор: Santiago E F T

10 апр. 2021 г.

The task are really hard even for a intermediate level

автор: Sneh P

26 сент. 2020 г.

This course is best but lectures are little bit faster.


19 мая 2020 г.

some assignment questions are too hard but informative.

автор: Paarth B

23 апр. 2020 г.

the pace and speed of teaching is fast according to me.

автор: Marco Z

11 февр. 2020 г.

The final tests are problematic in the evaluating phase