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

Оценки: 13,701
Рецензии: 3,101

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


Mar 16, 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .


Dec 10, 2017

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!

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251–275 из 3,030 отзывов о курсе Introduction to Data Science in Python

автор: Ryan B

Feb 04, 2017

The duration of the course (4 weeks) was ideal. It was manageable as a part time course. The tests helped me a lot to practice and learn the concepts deeply. The forums were very helpful in clarifying the questions. The video quality was great.

Many thanks for this great course which is made available online for free for all the world.

автор: Jonathan B S

Jan 13, 2017

Great introduction to pandas and the basics of data cleaning and preparation. The video lectures are great and the optional readings are interesting. I had a blast working on the assignments and learned quite a bit. I would recommend this as a good starting point to anyone looking to learn how to use python for data analysis purposes!

автор: Frederik W

Jan 24, 2017

The course is well structured and clarity of teaching is impressive. The assignments have a good mix of easy and progressively tougher questions that build on the syllabus and challenge you to manipulate data in your own way. I can warmly recommend this course to anyone who wants to begin manipulating and analysing data using python.

автор: oubouzar

Dec 27, 2016

Thank you very much for this course. I really enjoyed the level of the course. In particular the fact that a decent amount of research was needed to work on the assignment.

A few issues with the programming assignment. Especially at the beginning. I am assuming this is because this is the first version that uses jupyter notebooks.

автор: Pierre C

Nov 26, 2016

I learned A LOT during this course. I was even able to apply some of this knowledge at work after week 2 (and I do not have a technical job - I do this on my own time).

It did feel a little complicated at some times. Some more detailed explanations in the assignments could help. We don't always know what the autograder expects...

автор: Lokshyn O

Nov 21, 2018

Great hands-on course on Python pandas. The assignments are from intermediate to hard and instructions are not rather clear, but everything could be solved using pandas documentation and discussions forum.

The biggest advantage of the course is that it makes one think, dig documentation and practice pandas real-world examples.

автор: Guanghua S

Jan 23, 2017

This is a very well organized course with a great introduction to data science. In a short time of 4 weeks, it covers Python basics, Padans library, and some very basic introduction to statistics in data science. The assignments are well desgined, and the mentors are very helpful in the forums. I highly recommend this course.

автор: WR

Oct 09, 2019

Excellent course with learns you the basics of python for data science. Prof. Brooks has a very clear way of explaining things. Some experience with programming in for example R or Matlab comes in handy, especially for the assignments, so I would opt for a more introductory course to Python if you don't have that experience.

автор: Sandra D

Jan 10, 2019

Many of the questions in the Assignments were written in a confusing manner thus requiring a LOT of time to figure out what the request was. However, the WHOLE course and the learning was absolutely outstanding. Thank you for putting this course together and the Forum information that helped to figure out the Assignments.

автор: Bruno Y

Feb 05, 2019

Very comprehensive introduction to Pandas. However, assignments could have been more clear and there are certain questions on the coding assignments that are problematic. For example, one question on Assignment 3 is (according to the discussion forums) subject to a bug that causes the autograder to incorrectly dock points.

автор: Hatim

Mar 04, 2019

Wonderful, wonderful course!

I had been very familiar SQL before I started the course. But now I can do everything I used to do in SQL (data cleansing, data manipulation, aggregation, ranking etc.), and a lot more, with Python.

I now feel very comfortable with Python and looking forward to do more with this knowledge.

автор: Alan J

Jan 27, 2018

What a fantastic course to get you into data science. Real world examples, relevant discussion articles on ethics and privacy. Just make sure you know some Python, or are an experienced programmer as there is a lot of "applied" work to make you really learn things, and you need a good structured problem-solving mindset.

автор: Abdul B M

Apr 08, 2017

I got the opportunity of learning Python Basics through Dr Chunk's Python for Every Body, Now through this course I got the hands on experience of working with Data in Python using NumPy and Pandas, ya Its awsome journey overall. Thanks Coursera and University of Michigan for bringing us such a great Learning opportunity.

автор: Zhang T

Nov 27, 2016

Really handy and useful materials. However, if we can share our codes online after receiving the certificate will be really helpful. Cause although I finished the course, I still find some of my code is repetitive and not pandorable, and I would like to learn from other talents. Thanks Coursera and University of Michigan.

автор: Lucas S C

Dec 25, 2016

The project that is the end assignment is a very interesting exercise with real life application of information that is readly available to the public for real-world decisions.

Aside from that, it is a great course that scratchs the surface of what Pandas can do and open wide open all the possibilities it can give you :D

автор: Vincenzo P E B V

May 31, 2019

Un curso con un gran enfoque para comprender las bases de la data science y empezar a desarrollar la forma de pensar de un científico de los datos, aportando no sólo las herramientas técnicas necesarias sino también éticas y morales para ser profesionales integrales en nombre de las ciencias, la conciencia y la virtud.

автор: Sameer G

Mar 23, 2019

excellent course! learned a great deal of things. before-hand knowledge and basic python and basic stats helped. Perfect course for a beginner wanting to learn data science. The assignments were slightly more difficult than what i expected but the discussion forums helped a lot when i was stuck. Highly recommend it.

автор: Kalle H

Jul 10, 2018

Excellent course! Some experience of using Python is required beforehand and the recommended course at UM on coursera is an excellent start. This course give you a short but effective introduction to to overall structure of Python, how to use the pandas library and associated data types as well as some use of numpy.

автор: Illia K

Nov 24, 2017

It was my first python experience ever, so it was hard. But the course materials are very well described and detailed, so if you are motivated enough - you definitely can do it and enjoy it. Also all knowleges are applicable to real life since the very first week, so this course is really helpfull. Highly recommend!

автор: Shomari M

Nov 11, 2018

Great introductory course to using python for a (more or less) full data science project ! Of course much more can be done, but this course serves as a good intro Numpy, Pandas and some basic statistical operations from SciPy that build a solid foundation for expanding on the data science process in other courses.

автор: Changyu G

Apr 20, 2019

A quick introduction to Python and Data Science. The assignments are not as easy as you might think. To those who feel the assignment of Week 4 daunting, keep going -- data cleaning per se is not a difficult task yet a somewhat tedious one.

Thanks to the course team. I shall continue towards the following courses.

автор: Nathaniel S

Nov 26, 2017

I'd been hacking with pandas for a while, but I never felt I'd truly grasped it. In fact, I'd often switch to using multi-dimesional numpy arrays instead of dataframes. After taking this course, I now fully understand how to use pandas dataframes and will be using them regularly for data analysis going forward.

автор: Benjamin S

Jul 18, 2017

This was a really interesting course. The homeworks were very challenging and took longer than I anticipated, but because of this, I learned a lot. The only complaint I would say is that I posted a question on the forum and never received a response. I wish there was a better way to get questions answered.


May 05, 2018

I am an undergraduate Physics student who intends to delve into the remarkable field of Data Science and Machine learning. I think this course is an absolute beauty to beginners like me. I am glad that I found this course. The lectures are wonderfully delivered and each and every concept is nicely explained.

автор: VARUN V

Nov 01, 2019

Very good course. The Instructor is very good at explaining the concepts. The content in the assignments was very well chosen and help in getting a better understanding of the concepts. The teaching assistant was also good at explaining. All in all a very good introductory course... definitely recommended!