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: 26,484

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


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.

Фильтр по:

4551–4575 из 5,805 отзывов о курсе Introduction to Data Science in Python

автор: CHAKSHU G

18 янв. 2017 г.

Finding optimal solutions for the assignments would have helped more

автор: Laura V T T

16 мая 2021 г.

Great introductory course, easy to follow and challenging exercises


3 февр. 2021 г.

I think some feedback on assignments would be helpful for progress.

автор: yotam h

22 мар. 2020 г.

great course! highly recommended if you like struggling by yourself

автор: nitin R

19 мар. 2020 г.

Course content is really good but can be explained in a better way.

автор: Vishen M

18 окт. 2017 г.

Really enjoyed. Assignments take a lot of time, but you learn alot.

автор: Ariana C

17 авг. 2017 г.

Assignments need to provide better feedback when there is an error

автор: Vignesh R

8 авг. 2017 г.

Assignments are really good.Video Tutorials could have been better.

автор: Giannis A

29 дек. 2016 г.

Nice lecture. Needs to have more videos and more advanced tutorials

автор: Naymur R

14 июля 2020 г.

The Course Syllabus was too much good and better lecture quality .

автор: Veeresh I

31 мар. 2020 г.

Good course to learn the basic concepts to start with Data Science

автор: Sean L

18 окт. 2019 г.

Learned a lot, but mostly by self-learning when doing assignments.

автор: Yufei H

14 мая 2019 г.

Chapter 2 and 3 are good for me, the rest chapters are too simple.

автор: Ashley R

20 нояб. 2018 г.

some questions were vague but i guess thats part of the real world

автор: Aliyu A

12 сент. 2017 г.

A very good course. recommended for a intermediate data scientists

автор: aaron_lang

27 июля 2017 г.

Overall, the course is pretty good in terms of practice questions.

автор: Elana A

22 мар. 2017 г.

Great course and valuable information, but frustrating autograder.

автор: soham v s

3 нояб. 2021 г.

it is good course for beginers , jupiter notebook is also a good.

автор: RUBY P

2 авг. 2021 г.

It is a good course to attend and start your data science journey


24 июня 2021 г.

it was a nice course helped me understand more about data science

автор: Sangram K S

13 июля 2020 г.

It was good. The session can be more interactive and interesting.

автор: Gian C T G

25 июня 2020 г.

Need more excersices examples, some homeworks are quite difficult

автор: Subha M

31 мая 2020 г.

The course was good. But few points were not that up to the mark.

автор: Anil K C

6 мая 2020 г.

Good assignments to get you to learn the Pandas library in python

автор: Sadia a S

21 мар. 2020 г.

It is a helpful course for working with python for data analysis.