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

Оценки: 25,138
Рецензии: 5,612

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:

3901–3925 из 5,557 отзывов о курсе Introduction to Data Science in Python

автор: Stefan

27 янв. 2017 г.

Good course, if a bit fast paced, expect a great deal of searching through documentation and stackoverflow, but it is to be expected from an intermediate level course.

автор: Muhammad E

29 июля 2020 г.

as advertised this is not an introductory course , you need to know a little about python pandas and numpy before taking this but overall it's nice challenging course

автор: Marina L

28 февр. 2017 г.

A bit short, but good info. I wish you got access to an optimal code for each of the assignments once you submit yours and pass, so you could see how you can improve.

автор: Muhammad A

19 июня 2020 г.

Too much content covered in a video at very fast pace. I am comfortable with little long videos with more details on the topic and I think that can enhance learning.

автор: Haijian H

8 мая 2020 г.

The assignments are challenging and thus rewarding after hard work.

More explanation effort can be invested during the lecture would make the course perfect, I think.

автор: Robin K

27 апр. 2020 г.

A very useful course for getting to know Pandas and its application in data science. Bit of advice: use the online version of the notepad to avoid autograder issues!

автор: Christian L

18 окт. 2018 г.

I dont put the biggest mark because sometimes you have spend a lot of time trying to resolver a problem with and csv file and it is something related with format....

автор: Braza

6 янв. 2020 г.

This was a great course. But I would advice programming newbies to really be comfortable with problem solving and Python programming before going through it.


автор: N. K

26 окт. 2019 г.

The data could be made available. That available in the links have been updated and the code does not apply to the dimension of dataframe mentioned in the notebook.

автор: Sanjay V

1 нояб. 2020 г.

Good course. makes you work, but the learning was worth it , especially for someone like me who has ben struggling to pick up python though I am fairly good at R.

автор: Siddique Z A

15 сент. 2020 г.

Nice and very much informative session on Data science using python where we learns a lot and also completed assignments which is really a tough level assignments.

автор: Chimobi O

10 дек. 2019 г.

it's a nice course, more project based than theoretical, challenging assignments and good instructors. it spurs you to do a lot of research and individual learning

автор: Michel H

28 нояб. 2019 г.

Es un buen curso. Me parecío demasiado rápido el teórico y demasiado escueto. No me gustó que en los assignments hubiera que buscar tanto dato en fuentes externas.

автор: Ravva A K

23 июля 2019 г.

if anyone want to learn data science through practical approach then with no second thought enrol to this course .

thanks to cousera for providing me financial aid.

автор: Kaya Ö

15 апр. 2019 г.

Most of the work is on your shoulders, I think it needs more practice session on pandas. Wes McKinney's book are strongly recommended for help through the course.

автор: Prabhsimar S

14 окт. 2017 г.

It took a lot of self-study, practice and much more hard work than expected at start of course. But at the same time it increased my knowledge manifold. Worth it!

автор: Kapil C

11 авг. 2017 г.

The course structure was very good! Assignments were exciting although a one or two questions were not so clear. But the discussion forum was awesome and helpful!

автор: Timothy O

30 апр. 2017 г.

Great course! Some of the homework questions seemed a little ambiguous but I was able to find clarification in the course discussion. All in all I learned a lot.

автор: afsane h

10 мар. 2021 г.

This course is wonderful! I think its a good practice for those having some experience with python's pandas and numpy library, to make their a solid foundation.

автор: Christopher S

23 янв. 2021 г.

I would say an advanced level of python understanding is required. The assignments are very difficult however you do learn a lot about python and it's libraries.

автор: VIRAJ V P

29 мая 2020 г.

This is my first online course the course has indeed helped me to master data science and the assignments are quite good based on self learing more

Thank you...!

автор: Zhuang Q

6 нояб. 2019 г.

This course taught me a lot about pandas. However, the difficulty of the assignment didn't match the content of the lecture. It is too difficult for a new comer.

автор: morten o j

10 февр. 2018 г.

Steep intro, can be tricky to understand, the requested format of the responses. The autograder is not always verbose enough...

Good learning experience otherwise

автор: Dr. K A K

18 окт. 2017 г.

Good course - fast paced and needs a lot of self learning from the web to get through the challenging assignments. Be prepared to spend good time on this course.

автор: NASHA A

24 июля 2019 г.

I think it would be more interesting to include more diagram/map mapping instead of lecturer's image all the way from the beginning till the end of each lesson.