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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: 13,655
Рецензии: 3,094

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

AU

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!

SI

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 .

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201–225 из 3,024 отзывов о курсе Introduction to Data Science in Python

автор: Sean Z

Dec 30, 2016

Excellent course for data analysis in python, although the assignments are quite challenging and time consuming for beginners. During the course, I wish I could access to the correct codes after passing minimum score so that I could compare what I did with what common practices would be. We all code in different ways to achieve the same outcome, but it would be nice to know the most efficient ways/styles.

автор: Nick P

Jun 18, 2017

One of the best Python/intro to data science courses online. The assignments were sufficiently challenging and realistic, and I certainly learned new skills by completing them. I also appreciated the links to the articles and podcasts that gave me new perspective on my work. Also, a big thanks to Sophie and the other moderators on the discussion board, as the existing discussions were incredibly helpful.

автор: Tanmay T M

May 31, 2019

Everything is taught from scratch, which makes this course very accessible- still requires effort, however will leave you with real problems,confidence and understanding of subjects covered.

It was very helpful and easy to learn.The quiz and programming assignments are well designed and very useful. Thank Prof. Christopher Brooks and Coursera and the ones who share their problems and ideas in the forum.

автор: Peter B

Jun 23, 2017

Very informative course. It's a little fast paced but you can always go back and watch the videos again. It teaches the basics of pandas with a focus on how to prepare your data before starting working on it

You certainly need to do your own research (Google, StackOverflow, pandas documentation) to complete the assignments.

The mentors on the forums are the best! Without their help I would have been lost.

автор: Cameron F

May 02, 2017

I appreciate this specialization's patience to begin teaching data science with such a thorough introduction to handling data in python. The lectures are concise, with 80-90% of my time time spent on the assignments. The creators of the course have a clear understanding that most of a data scientist's job is spent cleaning data, and it's incredibly important to get the practice offered by this course.

автор: Hari G S

Jul 30, 2019

One of the most satisfying and challenging online courses I've ever taken. It's a densely-packed, fast-paced course and the assignments can be a bit challenging. For the assignments, we are provided datasets that are similar to the ones that we are likely to encounter in the real world. This course also teaches us to refer the official documentation and where to look for when we encounter problems.

автор: Tucker S

May 09, 2019

This course was excellent! It is hard to believe this is an introductory course given the difficulty, but this course touched on all of the skills I was looking to improve as an amateur programmer / data scientist. I would highly recommend this to anyone who has a base knowledge in python / pandas, and I very much look forward to the other courses in the specialization. Thanks Christopher and team!!

автор: Milan C

Jul 01, 2017

The course is very well structured from notes to assignments. Lecture content is to the point and lecture length is just right.

A lot of work has been put into the Assignments and Juniper notebooks. This element makes the course invaluable as you learn through practical experience. through well thought out and planned questions.

Thank you for making this quality of education available to all.

автор: Abdoulaye B

Nov 08, 2019

I have learned a lot from this course it is maybe the best course or one of the best so far. I come from a French-speaking country I learned English for six months before taking this course . However, what I like the most about this course is the way he is speaking.

I thoroughly recommend this course to everyone who wants to go for a career in Data Science because it is an excellent course.

автор: Nuno S

May 21, 2019

Excellent course for students with some knowledge of Python, but not for the complete beginner. The assignments revolve around using pandas with real-world data and are the best way to solidify what was learned in the lectures. The exercises can be time-consuming and you'll end up perusing Stackoverflow and the pandas documentation often. It's nevertheless an investment that pays well off.

автор: Kevin L

May 28, 2017

Excellent course, and very well taught. The projects are a bit difficult for beginners and will require independent learning as well as revising the lectures, but such is anything important in life.

The only thing I think the course can benefit from is a printed summary of lectures, since they can be quite dense with information! But I think the Jupyter Notebooks are a good inclusion as is.

автор: Matt W

Mar 02, 2017

I overthought some of the homework (the forums will tell you to not do that) and wasted much time going a bit too far cleaning data, however my own hubris aside, it was a good course. I've been working in NNs for some time, but wanted to use more formal data science tools on top of that and add something to my CV. I wish these tools had been around when I was in grad school... le sigh.

автор: Aditya V

Jun 11, 2018

This course has been very helpful and has motivated me to pursue more in this field. Most of my concerns and doubts are addressed in the videos, the instructor's explanation is very clear and understandable. The only suggestion I have is, to lay a little more emphasis on the python terms pertaining to data analysis, so that the student will have a better understanding and memorizing.

автор: Abhilash V

Dec 24, 2016

A great practical course.This course will make you think and search a lot on stackoverflow,which is good because a lot can be learned by doing it ourselves.Then why this course because we need to know what to look for and this course gives us the basics and we will be able to do the assignments by ourselves .Its not really tough but will need some time to get all the answers correct.

автор: chenmeng

Jun 17, 2017

Well, this course is quite good. It's obvious that the staff put a lot of effort into the course. They answered students' questions and solved problems which helped a lot. I learned basic programming skills of Python and the usage of library of Pandas. The professor gave the outline of what you need to do and the most of the work is done by yourself. Very happy to take this course!

автор: alex s

May 24, 2017

A very clear introduction to using Pandas for handling data. The integration of Jupyter Notebooks in both the assignments and the in-lecture pop-ups was very effective. I also appreciated the balance of covering most of the material in lectures, but leaving you to track down some things for the assignments. I can only hope the next courses in this progression are this well done.

автор: Drew L

Jan 19, 2017

I'm an experienced data analytics professional re-skilling after being laid off. I really enjoyed this course. Professor Brooks' lectures were engaging and clear. I found the assignments to be great practice, although they were challenging for my level of programming experience.

I strongly recommend having some skill with python, particularly pandas, prior to taking this course.

автор: Baochun L

Jul 03, 2017

After studying the course of Andrew on Machine Learning, I want to study a course , which focus on python. I once chose the Machine Learning Specification , but the course use the non open source python packages. And I tried this course. I used about 4 days to finish the 4 weeks, and get myself familiar with pandas though I have no experience on python and pandas programming.

автор: Shawn M

Aug 25, 2018

Great overview of Pandas and ETL using Pandas and Python.

Assignments and final project were challenging and realistic in terms of how you might use Pandas and Python in real world situations.

The auto-grading of projects can be annoying with error messages that aren't clear or accurate. If you aren't clear why an answer isn't accepted, then don't hesitate to search the forum.

автор: Martin W

Jul 27, 2017

Excellent course with rich mixture of course material from useful video lectures, quizzes, links to published papers and supporting websites, book references, discussion forum and of course the interactive online assignments. I appreciated the course submission process and the ability to check and re-submit assignments. Cant wait to start the next course in the series.

автор: Julian O

Apr 16, 2018

Requires a tremendous amount of self-study and trial and error if you're starting from ground zero in terms of pandas knowledge, but the reward is a level of comfort and facility with pandas dataframe manipulation. Definitely a learning by doing experience. Cleaning datasets and manipulating dataframes turns out to be pretty fun once you start getting the hang of it.

автор: Niccolo A H

Aug 31, 2018

The course is challenging for a newcomer to Python. The instructors rely on the student's self-learning to fill in the gaps needed to solve the course assignments. It's been a great way, albeit a little stressful, way to learn. The course also does an excellent job of keeping the student grounded as to implement a high ethical standard when practicing data science.

автор: Shou-Chung W

Jul 06, 2018

This assignments of this course is most useful to solidify your knowledge, and ability to self-study. When in doubt, use Forum, as many students past and present have all shared your frustration and most of all everyone's learning experience, which make this course a great one! Thanks to all instructors, teaching staffs, and fellow students, you guys are wonderful!

автор: Maitree R

Jun 09, 2018

It's a nice course for Beginners in Python Programming and who have interest in Data Science. It requires a little dedication and lots of programming. The Discussion Forum is amazing it has everything and special thanks to the Mentors Sophie and Yusuf during the assignments. It requires lots of self-learning and a little research for every programming assignment.

автор: Jim

Aug 03, 2017

Python is huge. Course helps you focus and apply Python to data science.

Me? was new to Python; was novice at programming; had strong background in math and business (both helpful, but not prerequisite); read "Python for Data Analysis" by Wes Mckinney to supplement lack of programming experience -- focused on numpy and pandas chapters; frequented stack overflow