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

4.5
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Оценки: 24,706
Рецензии: 5,542

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:

3926–3950 из 5,487 отзывов о курсе Introduction to Data Science in Python

автор: Harsh G

3 июня 2020 г.

Last Assignment which is Hypothesis Testing could be more elaborated and more reading material could be provided there for better understanding.

автор: Jatin R

16 мая 2020 г.

The course was Great. You got to learn so many things. The assignment is so challenging it will definitely increase your knowledge for the same.

автор: Víctor A M G

27 янв. 2020 г.

Very difficult course, very challenging in terms of the validation tool for the homework, but undoubtly I learned very much from it. Thank you !

автор: Amol V B

7 янв. 2019 г.

I would like to refer to all beginnner.. coursera is the best content to learn data science and Machine learning..

Amol Billale

AI & ML Researcher

автор: augustus e

11 мая 2020 г.

Great course. I'll recommend changes for the assignments. Some were really vague, especially with the workings. It made them quite challenging.

автор: Wynona R N

7 мая 2020 г.

This is a good course. It is challenging yet fun. Instructors are very helpful for the assignments. I believe I learned a lot from this course.

автор: Pawroosh M

9 сент. 2019 г.

I feel the pace of teaching the coding pieces should be slower and clearer. However, overall it is a decent jump-start to learning data science

автор: Ashutosh S

5 мая 2020 г.

The course was great though the assignments should have more clarity in terms of the questions and language ambiguity should be taken care of.

автор: Purvansh s

31 мар. 2020 г.

It was a great experience to be a part of this course, the explanation was awesome, the hands-on practice was superb, I loved the course alot.

автор: lazar m

17 нояб. 2019 г.

I learned a lot about Pandas (Dataframe and Series), it's a powerful library. However the course didn't dig enough the statistics part. Thanks

автор: Mariusz K

10 нояб. 2019 г.

Too little of expounding and too much of searching the net by oneself. Too few examples. It is a self-learning but what's the Course for then?

автор: Hungy Y

9 авг. 2017 г.

Do more examples & explain more theory on screen, rather than have the camera focus on the lecturer.

Highly useful intro tutorial. Thanks team.

автор: Tanishk S

17 июня 2017 г.

if you are new to the field this should be in your way to excel. had a great time . pls do refer to the books suggested it is surely necessary

автор: Rahul K

23 апр. 2021 г.

Great course with everything well explained.

Its just the assignments are a bit tough and you have to explore a lot to get the answers right.

автор: 21_Keshav M

5 авг. 2020 г.

The Structure of Course is Great!! Although I would love to have mentors explain concepts a little more. Overall a great introductory course.

автор: Stefanie N

25 нояб. 2017 г.

The help in the forum was good, the assignments were fun although I always had some problems with the grader at first, some resolved some not

автор: Roshni G

2 февр. 2017 г.

The assignments were challenging and cool. Lot of self-study needed to crack them. The lecture videos could have been a bit more interesting.

автор: ASHISH B

3 июля 2020 г.

The assignments were very interesting and the teaching also was very good. The main help was the provision of notes in the jupyter notebook

автор: Sven E

16 нояб. 2019 г.

assignments quite challenging , way more time needed than the est. times given by coursera. happy I could finish it. on to the next course !

автор: Marc

8 дек. 2017 г.

Curso interesante para iniciarse en la librería pandas. A veces vas algo perdido pero dedicandole esfuerzo y atención aprendes muchas cosas.

автор: Jason R

16 окт. 2017 г.

Could have been more challenging and worked with more interested bigger datasets but was a great way to get up to speed on pandas abilities.

автор: Paula C R

20 июня 2017 г.

The course is really nice, hands-on all the time. Some questions of the assignments could be improved to avoid ambiguity/subjectivity tough.

автор: Ishank T

31 мая 2020 г.

Not beginner friendly, great assignments which require "stackoverflow" skill. you actually learn from assignment. Videos are not that great

автор: Dominic l H

5 мар. 2018 г.

good course overall but there needs to be more information on code profiling/optimizing it is really required to pass a part of question 4.

автор: luciano d f a

26 янв. 2018 г.

A good introduction to Pythonic data science programming tools. Just bit too fast in exposition for my learning curve. However I liked it.