Chevron Left
Вернуться к Introduction to Data Science in Python

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

4.5
звезд
Оценки: 23,854
•
Рецензии: 5,354

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

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

SI
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:

4326–4350 из 5,272 отзывов о курсе Introduction to Data Science in Python

автор: JAYDEEP B

•
19 мар. 2018 г.

Too Tough for the assignments to complete

автор: Harshavardhan R

•
3 нояб. 2016 г.

Great pace for intermediate level people.

автор: RAMYA D K T

•
27 сент. 2020 г.

Learnt a lot .It is useful for my career

автор: Santanu B

•
27 мая 2020 г.

Explanations are too less in each module

автор: Bipin Y

•
16 апр. 2020 г.

The questions were harder than expected.

автор: Andreas H

•
29 мар. 2020 г.

Translation into german would be helpful

автор: Mengjie

•
22 мар. 2020 г.

a little difficult for me，but gain a lot

автор: Dr. D S A

•
13 дек. 2019 г.

The Assignments are little bit difficult

автор: Chethan S L

•
27 мая 2019 г.

Course content is excellent and helpful.

автор: Zhong H

•
21 нояб. 2017 г.

Basic information about numpy and pandas

автор: Devashish N

•
12 февр. 2017 г.

Nice course for understanding the basics

автор: Sean M D C S

•
4 янв. 2021 г.

Very good course with great instructors

автор: NIKKETHAN R

•
3 июля 2020 г.

Excellent course and somewhat difficult

автор: Daniel M

•
5 июня 2020 г.

Very strong base. Difficult assignments

автор: MRUNAL A

•
4 июня 2020 г.

amazing knowledge about numpy and panda

автор: Prince M K

•
25 мая 2020 г.

The pace was of the course was too fast

автор: Sanchita S

•
10 мая 2020 г.

For A beginner ,it was a great course !

автор: June L

•
9 мая 2019 г.

It is good but also very very difficult

автор: Howard Z

•
14 мар. 2019 г.

A lot of information but extremely hard

автор: Youri D

•
29 янв. 2017 г.

It was very hard but extremly learnful.

автор: Weizhi L

•
6 сент. 2020 г.

The skills I learned are quite useful.

автор: Sathyanarayana V

•
9 мая 2020 г.

The online platform has trouble saving

автор: Narendhra G

•
5 мая 2020 г.

Thanks for the giving good stuff to me

автор: Kevin D

•
18 мая 2018 г.

Challenging and worthwhile for a MOOC.

автор: Smit D P

•
28 апр. 2020 г.

Some assignments questions are tough.

Coursera Footer

Лучшие онлайн-курсы

Лучшие онлайн-специализации

Сертификаты онлайн

Программы получения онлайн-дипломов

Coursera

Сообщество

Еще

Учитесь, где угодно
Загрузить из App StoreЗагрузить в Google Play