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: 24,688
Рецензии: 5,539

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

AU
9 дек. 2017 г.

Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!

Фильтр по:

3976–4000 из 5,483 отзывов о курсе Introduction to Data Science in Python

автор: PeiDa K

8 сент. 2017 г.

Tough course. Great exercises increasing in difficulties and are without much training wheels. The videos are a bit too fast for me.

автор: Alexander C

19 мар. 2017 г.

I would like to have seen more detailed teaching on Hypothesis testing and how it applies to python before tackling the final project.

автор: Yang Q

24 окт. 2018 г.

The assignment wordings are ambiguous. Clear instructions are needed with a sample of the end product showing data type/format/shape.

автор: Qihang Z

29 мая 2020 г.

If technical points can be explained in more details, the course will be more attractive. Overall, it's a very fantastic experience.

автор: Ken I

17 мар. 2020 г.

I had to rely on the feedback from the forum for the final week's homework. It was impossible without reading everyone's questions.

автор: Shanaka J

18 апр. 2019 г.

this goes through the basics once again. a very good course to brushup the forgotten python scripts on data handling and cleaning...

автор: chetan

4 июня 2020 г.

My humble request is that content should be more elaborated with examples so that its clear as what the instructor wants to convey

автор: Koffi M K

11 июля 2019 г.

Very good course to manipulate data with python. My only issue is that the assignments need to be elaborate or described in better.

автор: Randson

18 июня 2017 г.

I think the questions should be better explaneed in the anouncement at the avaliations. Especially whats is expected by the grader.

автор: DİLARA Ş

24 мая 2020 г.

It was so challenging for an introduction course. However, it helped me a lot to improve my skills in Python Pandas. Thanks a lot.

автор: hai h

25 нояб. 2019 г.

The course is good for learning new in Data Science, but some exercise should not to difficult and correct how to check the result

автор: Grigory M

29 сент. 2019 г.

My review is actually 4.5, which I cannot enter. Would rate as 5, but unclearness of the final assignment made it too frustrating.

автор: Dentko, T

21 июня 2019 г.

Sometimes grader was too picky and i spend many many hours trying to figure our mistakes, that were only wrong datatype and so on.

автор: André Y

16 мар. 2019 г.

The course is great, there are challenging assignments, great for those who want to learn the basics of programming/data analysis.

автор: Venkataraghavan P K

10 февр. 2019 г.

The assignments were pretty good, making one to go advanced into python. The teaching could be bit slower paced with more content.

автор: Saumitra K R

8 сент. 2017 г.

Nice course for intermediates and beginners.This course becomes quite challenging and difficult to grasp as the course progresses.

автор: Francisco C

30 янв. 2017 г.

All the ingredients are there, but it would be nice to have more hand-holding given the ramp-up in difficulty in only a few weeks.

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: Colton L

4 окт. 2021 г.

programming assignments and quizzes were tedious. I think best way to learn syntax is generally learn by doing. Class was decent

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.