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

4.5
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Оценки: 25,646
Рецензии: 5,715

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

YY

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.

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

Фильтр по:

4501–4525 из 5,665 отзывов о курсе Introduction to Data Science in Python

автор: Christopher J

19 июня 2020 г.

Excellent course, though the interpreter needs to be updated.

автор: SHIVANG S

4 мая 2020 г.

Very difficult for those who are new to this numpy or pandas

автор: Sahil S

2 февр. 2020 г.

satisfactory,

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..

автор: SUDHANSHU Y

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: 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