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: 25,680
Рецензии: 5,721

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

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.

Фильтр по:

5051–5075 из 5,673 отзывов о курсе Introduction to Data Science in Python

автор: Abhishek K

20 февр. 2018 г.

The assignments are pretty brain storming.If you want to practice some wrangling with data I would recommend it,but you must have some basic python knowledge along with some skills using pandas and numpy.

автор: Chad H

12 авг. 2019 г.

Issues with the unforgiving autograder require spending hours (unnecessarily) reading discussion forum for precise matching of string formatting. This type of issue destroys the momentum of the course.

автор: Amit S

20 июня 2021 г.

Way too tough for beginners or even intermediates lectures are very long which makes them boring and the assignments and quizzes are way too tough.Hope to see betteer course and much easier assignments

автор: Moustafa A M

3 сент. 2017 г.

I think we need to have more interactions into the lectures, also the material inside the course is not enough most of the course i do it searching and copy and paste the code from the online materials

автор: Leandro F C D

17 мая 2020 г.

The instructors did not explain functions well enough, is like they were always in hurry to finish and go to the next lecture. I end up reviewing a lot of internet materials to finish the assessments.

автор: Marty D

16 окт. 2019 г.

Lectures spend a lot of time on watching a person talk to a camera. Projects are pretty good, though auto-grader is a pain to debug. TA & Moderators are excellent and so is community taking course.

автор: Caroline M

29 окт. 2017 г.

Good overall and I liked the instructor. However the assignments are extremely difficult, especially Week 4 and there are not a lot of online resources made available. Definitely not for a beginner!

автор: murray d

21 апр. 2020 г.

Really a struggle to navigate around the discussion forums. The autograder is also a huge challenge. If you can make the actual tests that it runs available up-front would save a lot of time.

автор: Yiyi C

23 июня 2018 г.

The course schedule is tight. I feel like a little bit hard for non-cs major learners. The good thing is you could still upload your homework even after the deadline before the last day of course.

автор: Jae H H

3 апр. 2018 г.

The course offers very little guidance. Nevertheless, I learned a lot but it's really not that well structured. The course also makes you do homework on something that is not covered in the class.

автор: Wei L

11 мая 2018 г.

i like the course content. but the assignments need improvement as i wasted lot of time due to unclear instructions. also if the professor can compile more content into slides that will be great.

автор: Nidhin J T

25 сент. 2017 г.

It’s very fast paced. Personally I would prefer to spend more time on each topic particularly since it deals with the basics of data science and is very important to understand each topic clearly

автор: Alexander K

17 янв. 2017 г.

Skills acquired when finishing this first course are very useful and applicable. However, lectures and assignments are almost unrelated. This course is nothing for people who are new to python.

автор: Ruban S

7 апр. 2019 г.

The coursework validation could use some work to be more concise with error messages but it's OK as long as you work with it.

Content is good and seems to give a decent coverage to the basics.

автор: Luis V (

22 мар. 2021 г.

Great course, but the programming assignments take too long time and are more than python only assignments, researching about geography or where a team belongs to, that takes a lot of time.

автор: Mark E

14 мар. 2017 г.

This course relies almost exclusively on self learning of the details of pandas. It would be greatly improved by examples of how to use pandas to solve problems similar to the assignments.

автор: Kevin d V

6 дек. 2017 г.

I learned a lot. But be aware that programming skills are a requirement for this course and that you will have to research the web (stackoverflow, pandas documentation) on your own a lot.

автор: Sebastian R

3 дек. 2019 г.

Good course i.g! But it is quite annoying, that the auto grader (python 3.5 ?) does not behave like the online coursera notebook (python 3.6.2), which leads to errors at the evaluation.

автор: M J

21 дек. 2017 г.

Course material is good, covers the right topics to get started with python and pandas. Assignments and especially the grading process require a bit more patience than I was expecting.

автор: Kalle A

3 янв. 2018 г.

I enjoyed the course, but I think the exercises could be improved a bit. Especially in the last two ones could have better explanations and examples of what's expected from the answer.

автор: wilfried l

26 дек. 2019 г.

You will learn a lot, by yourself to solve the assignment.

Which could be see as a good way to learn

Time to do each assignment is clearly under estimated. You can multiply by 2 easily

автор: Juan C M

4 июля 2020 г.

Too much self-learning taking into account that this is supposed to be a course, could make example projects for better understanding instead of jumping right away to the assignment.

автор: Itzhak K

5 нояб. 2019 г.

The course was fine, but the last assignment was too hard for me. And I think that for Introduction to data science - the first course in the series it shouldn't be so complicated.

автор: Rhishikesh J

29 мар. 2018 г.

Amazing course for an introduction to the pandas library and its main data structures Series and DataFrame.

Improvements could be made to the hypothesis testing section of the course.

автор: Aarya B

15 сент. 2019 г.

Great explanation. But the speed of tutor is quite fast, so one needs to rewatch again and again. And for better understanding one has to practice questions from external resources.