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: 24,558
Рецензии: 5,516

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:

3976–4000 из 5,460 отзывов о курсе Introduction to Data Science in Python

автор: Omran A S S A R

13 июня 2020 г.

I loved the assignments but the video lectures lack all the info needed to do the assignments. assignments require self learning.

автор: Jinhang J

23 мар. 2020 г.

I wish we had more examples and datasets in this course. Overall, it is a good way to start and learn how to use NumPy and Pandas

автор: CR T

30 окт. 2019 г.

over all good content, assignments were good, one thing i find it hard is pacing, it's sometimes too fast, but it is worth taking

автор: Ivan Z

24 февр. 2019 г.

The course is not bad for the start, but I'm a little bit confused because of difference between lectures and assignments' tasks.

автор: Declan K

20 сент. 2017 г.

The assignments were a very good indicator of progress. The tutor was a great help for when I had a problem. Thanks a million ;-)

автор: SHUBHAM P

29 мая 2020 г.

Course could have been taught with some more depth and focus given on covering more concepts. Otherwise the curriculum was good.

автор: Mauricio

6 мая 2020 г.

I gues is important give more estructures to the student, i think a little cheatsheet of python is very useful for the students.

автор: Vijay R

7 нояб. 2019 г.

The assignments were a bit difficult. It sometimes demotivates when the going gets tough. Was able to crack it in the end though

автор: noiplee

3 авг. 2019 г.

Great courses,enjoy.But this is the hardest course I ever have on coursera.Slow down the speech and coding part would be better.

автор: Haotian H

19 февр. 2018 г.

course content is very good. the assignments need to be more detailed...some questions are confusing and need more instructions.

автор: SANJANA K

27 июня 2020 г.

It was a knowledgable experience. But I would say need a bit more work towards explaining the programming during the sessions.

автор: Hans C P

26 июня 2020 г.

It was difficult to choose; 4 or 5 stars. It is a 5 star course, but due to my fighting with the autograder, I ended up with 4.

автор: Anatolii L

13 апр. 2020 г.

Pros: Good and practical syllabus

Cons: no so clear explanations of some topics, problems unclear issues with assignment grading

автор: Mujeeb A F

18 июля 2018 г.

Course content was really good as it focused more on practical work rather than just theory. The last assignment was difficult.

автор: Apurv S

28 нояб. 2016 г.

Very good... but question should have been properly explained (in a detail manner).. overall it was a great learning experience

автор: Xinyang W

26 окт. 2019 г.

Video instruction is way too short compare to other Coursera courses. I don't think it's a good course for absolute beginners.

автор: Zhenying T

8 сент. 2019 г.

The lectures are a bit fast and there are a few errors in the homework. The homework is very helpful and uses real-world data.

автор: Karina L B

17 окт. 2018 г.

It is necessary to explain more some definitions and some assignment are not entirely clear. Excellent response from the staff

автор: Alain D

20 февр. 2018 г.

Good course, you have to do a very large amount of work and research and test on your side in order to properly understand it.

автор: James S

13 июля 2020 г.

Excellent course for introduction to pandas. Espacially the assignments offered in the course are great and very well picked.

автор: Jacob L

23 авг. 2019 г.

It was a good solid course on intro data science with Pandas. I found the videos were a little dry, but the content was good.

автор: Aditya M

25 июля 2019 г.

Overall you get to learn new and good ways of doing pands and matplotlib but its way too fast for anyone with basic knowledge

автор: SHUBHAM S P

9 февр. 2019 г.

Really good course for beginners in Data Science . The Faculty is very nice and explains each and every concept very clearly.

автор: EMRE D

2 авг. 2018 г.

Submissions were generally hard, if you want to take this course you should learn most of the programming things by yourself.

автор: Sang L

16 апр. 2018 г.

Good Intro part for pandas. The homework part is more difficult than the materials. Materials could have been more organized.