Chevron Left
Вернуться к Introduction to Data Science in Python

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

Оценки: 25,768
Рецензии: 5,734

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


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.


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:

4576–4600 из 5,687 отзывов о курсе Introduction to Data Science in Python

автор: Divya s

1 июня 2020 г.

it was a good course overall for a beginner like me!

автор: Mohammed E A M

8 мар. 2020 г.

Many times I found it hard to understand the problem

автор: Sam M

14 сент. 2019 г.

Great Intro course into both Data Science and Pandas

автор: Alfredo E d l T

22 сент. 2018 г.

A very course. Only little problems with autograder.

автор: Abhinav A

10 сент. 2018 г.

The pace of the course could have been a little low.

автор: Wang Z

6 нояб. 2017 г.

Videos are a bit short without detailed explanation.

автор: Rodolfo D

17 дек. 2020 г.

Muy bueno y practico para comenzar en este entorno.

автор: Niraj P

4 июня 2020 г.

Really effective in building my python programming.

автор: Ujwal G

22 мар. 2019 г.

assignmentds are much harder than d course content.

автор: Dale S

18 июня 2017 г.

Great way to learn about Pandas, Numpy and Jupyter!

автор: Leen P

13 апр. 2022 г.

sometiemes the questions are not detailed enought!

автор: Lazar S

7 янв. 2022 г.

There are some bugs but in general a great course!

автор: Deep C

29 нояб. 2019 г.

This course is advance level but very informative.

автор: Ali A

24 янв. 2019 г.

Good for people with prior programming experience.

автор: Rishikesh K

4 июля 2017 г.

The instructions for assignments need more clarity

автор: YASH B

24 авг. 2020 г.

Content is good and the assignments are on point.

автор: Aditya S

25 окт. 2019 г.

The assignments were quite tough and challenging.

автор: Nandakumar P

26 янв. 2019 г.

Really very mush useful for all the data analyst.

автор: Alok S

6 июля 2018 г.

Great content and explanations to novel concepts.


21 мар. 2018 г.

A very good course as introduction to Datascience

автор: Lionel C

28 нояб. 2017 г.

Great for learning python basics for data science

автор: Waqar Z

7 апр. 2017 г.

This is the good course for learning data science

автор: Alluru M

10 окт. 2020 г.

really helped in improving skills in our carrier

автор: ADARSH G

26 июля 2020 г.

The course should provide with some more videos.

автор: JAYANTH T

24 мая 2020 г.

It is one of the best course of data science...!