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: 24,275
Рецензии: 5,438

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:

4276–4300 из 5,367 отзывов о курсе Introduction to Data Science in Python

автор: Sahil S

2 февр. 2020 г.


although last week lectures need to be improved.

автор: Kartik K

2 авг. 2019 г.

Bit difficult for one who is not from programming background.

автор: David B

16 сент. 2018 г.

Interesting exercise if you're willing to trawl StackOverflow

автор: PRAKASH S

1 мая 2020 г.

There is a lot of scope for the improvment of vedio lessons.

автор: Nasir H

7 янв. 2020 г.

The content was high level and good. You should explain more

автор: Hannah

1 сент. 2019 г.

Good courses and exercices but difficult to submit sometimes

автор: Andreas B

27 дек. 2018 г.

Great course. Tasks being not precise is sometimes annoying.

автор: Snehasish S

12 мая 2018 г.

Course videos should be more and in detail for each concept.

автор: Manuel T

8 янв. 2018 г.

Quizzes do not match videos. Anyway, great course all in all

автор: Aaron W

29 сент. 2020 г.

Very good introduction. Assignments were really difficult.

автор: Karan S

14 мая 2020 г.

Was quite condensed and not explained fully in some places.

автор: Dhruv S

5 мая 2020 г.

Assignment 3 is very ill-planned rest of the Course is good

автор: Onur D

2 июня 2019 г.

Great content, just some parts need a bit more explanation.

автор: Рычков А В

17 апр. 2019 г.

Последнее задание, требует подгонки данных? Очень странно..


11 мар. 2019 г.

This course is best to start in Data Science for beginners.

автор: Purusharth A

12 мар. 2018 г.

Very effective course to start with Data Science in Pyhton.

автор: ANGEL A L B

31 июля 2017 г.

It has its problems, but it's a great start to Data Science

автор: bret r

3 дек. 2016 г.

Good content - some prior knowledge of pandas is important.

автор: Sanjay S

6 авг. 2020 г.

This was a good course. I recommend it. I learned a lot.

автор: Abir H R

10 мая 2020 г.

videos should be a more informative and Very hard exercise

автор: Haoyu 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: )