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Вернуться к Introduction to Data Science in Python

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

Оценки: 24,316
Рецензии: 5,447

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:

3976–4000 из 5,380 отзывов о курсе Introduction to Data Science in Python

автор: Mateusz M

25 сент. 2018 г.

The course is going pretty fast through the most important libraries. Make sure you understand python and statistics.

автор: Jaymin J

3 мая 2018 г.

great class to start journey to python data science. the exercise can be more clearly defined but, discussion helped.

автор: Shivam K

29 июля 2020 г.

Course is very interesting and video lectures ar worth understandable as well .

need to improve the timing of speech

автор: Theodor B

2 нояб. 2018 г.

It needs more examples of how things are done, so that all new key concepts are grasped before leaving for the next.

автор: Geoff H

28 сент. 2018 г.

Good info and subject matter. Be prepared to spend a fair mount of time coming up with ways to practice on your own.

автор: Alejandro M S

1 апр. 2018 г.

Assignements could be explained better (Maybe i'm not english native speaker), but i learnded a lot withnthis course

автор: Rahul M N

1 мар. 2021 г.

An excellent course to get started with Data Science, Topics were well communicated and illustrations were intutive

автор: Yair Y P V

28 июня 2020 г.

Buen curso, las actividades son mas difíciles de lo enseñado en clase pero sirven para mejorar el conocimiento base

автор: Carlos A V T

6 июня 2020 г.

Great course, the exercises are a little bit confusing, but you need to read the forum to get the right directions.

автор: A H

24 мая 2020 г.

Great course really, and a great Tutor. I just I feel emphasizing more about certain subjects would've been better.

автор: Ian B

7 мар. 2020 г.

I would give 5 stars if the developers update to the latest version of pandas. It was a bit annoying to use 0.19.2

автор: Yunhao Z

18 июля 2017 г.

Very good course to learn data analysis with Python. The programming work is a bit challenging for Python starter.

автор: Dmitry G

16 нояб. 2016 г.

Pace of lectures is rather fast and doesn't fit to homework level (which is much harder). But overall course is OK

автор: Ricardo H

26 сент. 2020 г.

Should have more detailed docs as resources, mainly about Pandas. Something like the weekly notebooks elaborated.

автор: Ekun K

17 июня 2020 г.

This was a very tasking yet interesting course for me. I loved the challenges, follow up quizzes and assignments.

автор: Saori Y

17 мая 2020 г.

The course was good! However, assignment auto grade sometimes does not work because of python version difference.

автор: Luke F

9 мая 2020 г.

autograder can be tough and a little unforgiving, but I understand the difficulties. Course pretty good over all

автор: MAMADOU O L

2 февр. 2020 г.

It was a great experience, i leaned a lot, but some questions were a little bit confusing,try to fix that please.

автор: koalaahana

8 сент. 2019 г.

great lecture, try to deliver lots of information in 4 courses. would be helpful too have more hands on practices

автор: Elizabeth M

27 сент. 2020 г.

More time consuming than advertised. Good overview. Lighter on the stats, and heavier on the coding in python.

автор: Raulindo S S N

22 июня 2020 г.

It is indeed a great course for those who already have some programming skills. The instructors are really good.


30 мая 2020 г.

The explanation of the code written and methods could have been much more elaborate for understanding it better.

автор: alain m

29 янв. 2018 г.

Un cours intéressant avec des exercices (assignements) plutôt complexes parce que peu guidés. Un vrai challenge.

автор: Artem N

28 апр. 2017 г.

Tasks sometimes a bit tacit to understand what exactly should we return and in what format, but course is great!

автор: Sneha S

2 июня 2018 г.

The course outline is good, though there can be some more details about submitting the answers to the questions