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: 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

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

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:

3951–3975 из 5,483 отзывов о курсе Introduction to Data Science in Python

автор: Sirajalam S

20 авг. 2020 г.

The course is very interesting and quite informative. I got a lot of information about Data Science and its application in various fields.

автор: Germano R

23 мая 2019 г.

Great course for beginners, as well as for those with previous data science experience with other programming languages (i.e. R Computing)

автор: Manas A

25 дек. 2018 г.

Overall a really great course with a great deal of skills and information, but i wish the coursework assignments were a little bit easier.

автор: ALISON J D

3 янв. 2018 г.

The course was challenging but fun. To complete the assignments you need to research python on the Internet and consult the course forums.

автор: Eduardo S J d P

26 нояб. 2016 г.

Autograder is hard to understand and has no feedback. Could improve the feedback mechanism, maybe with peer review. Thanks for the course!

автор: Md. N K S

23 июля 2020 г.

Assignment 3 and 4 was much difficult then others, I have to submit 3 times and have spent more then 7 hrs. Ultimately i have learn good.

автор: devansh v

21 июня 2020 г.

The course is really good but a little more insight to pandas would have made it even better and also the auto-graders is a little buggy.

автор: MUSTAFA Ö

23 апр. 2020 г.

Assignments of the course are more educative than video contents . Because videos include short and insufficent information about topics.

автор: Indranil B

8 июля 2017 г.

A good course overall.The assignments are challenging and promote a lot of self learning.The Jupyter Notebook integration is also a plus.

автор: Martin D

19 окт. 2020 г.

Very good explanations of course material, interesting assignements, but some instructions in graded assignements were not always clear.

автор: Misa

28 сент. 2018 г.

Overall very good. Like the lecture styles. Some of the questions in the assignments aren't clear, but the discussion forum helps a lot.

автор: Cosmin P

19 янв. 2018 г.

Good training for beginner. The last assignment seems to be quite challenging but once delivered helps a lot to increase the confidence.

автор: Paula V

15 мая 2021 г.

This course is was very challenging since I have to pretty much learn python on the fly and then understand the data science part of it

автор: kartik m

28 мая 2020 г.

It provides you with very good learning experience , though i felt for introduction to data science , the assignments are little tough.

автор: GRACE B

17 июля 2018 г.

Course videos provide good examples of using methods, but prepare to teach yourself from StackOverflow when completing the assignments.

автор: Soham S

7 дек. 2017 г.

Good course to start learning python and some of it's application.

Week 1 and 2 videos are very fast forwarding on python for beginners.

автор: Khushal K

4 дек. 2017 г.

The demo speed is too fast for the new average learner, but we can always stop and rewind. Assignments are lengthy yet too informative.

автор: Leon V

8 февр. 2017 г.

Don't think this should be classified as "Beginner Specialization. No prior experience required." Need at least some coding experience.

автор: Qinzhe Z

4 нояб. 2016 г.

To be honest, I think the course is very good, however, it may be need to more clear on the description of the questions in assignment.

автор: Houssam B

21 июля 2021 г.

T​hank you for this amazing Course, I really learned a lot during the entire 4 weeks. everything was easy to learn and well organised.

автор: Andrii M

5 сент. 2020 г.

The course is good, but the autograder is absolutely horrible, spend hours figuring out how to force autograder to accept my solution.

автор: Huseyn G

14 июня 2020 г.

Generally, it is very useful course, and provides lots of resources. However, I believe that they are areas to make the course better.

автор: Deleted A

26 окт. 2018 г.

The assignment is quit hard and students need to do a lot of research to pass. But you can learn a lot of things through this process.

автор: AnirbanBanerjee

14 июня 2018 г.

I loved problems and approaches. There are definitely some key topics which needs more practice, hopefully with time this will evolve.

автор: Spenser P

22 апр. 2018 г.

There was a lot of self learning required to complete the projects, I'm not sure the lecture portion of the course is worth the money.