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Opiniones y comentarios de aprendices correspondientes a Introduction to Data Science in Python por parte de Universidad de Míchigan

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Acerca del Curso

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....

Principales reseñas


9 de may. de 2020

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


28 de sep. de 2021

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

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426 - 450 de 5,725 revisiones para Introduction to Data Science in Python

por Harish S

12 de ago. de 2020

One of the best courses i have taken up so far.I am really happy to complete the course gaining a vast knowledge in Data Science at the same time improving my python programming skills. I cannot express how good was the instructor(Christopher Brooks) and also i really thank University of Michigan for providing this course. I would really recommend this to my colleagues and friends . Thank You.

por ammara r

14 de jun. de 2020

This was an extremely well designed course. Assignments were very challenging and I had so much fun doing them. Solving the assignments give a true sense of accomplishment. Special thanks to instructors and mentors who help students in understanding the assignments. This course could not have been completed without their help. Thanks to University of Michigan for offering this specialization.

por Andres M

15 de jul. de 2022

E​xcellent course! It is demanding, as you need enough time to read the complementary material (book by Wes McKinney) and for the assignments. The videos of the instructor typing in the markdown cells as closed caption is not very didactic. Although what he says is absolutely relevant. The assignments are challenging and requires more time than what Coursera suggests (about 3h / assignment).

por Milan C

1 de jul. de 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.

por Abdoulaye B

8 de nov. de 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.

por Nuno S

21 de may. de 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.

por Kevin L

27 de may. de 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.

por Matt W

1 de mar. de 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.

por Aditya V

10 de jun. de 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.

por Abhilash

24 de dic. de 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.

por chenmeng

17 de jun. de 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!

por Shihui W

5 de abr. de 2020

It is too hard as a second course after 'Python Basics', I have to admit that I search a lot of tutorial to pass the assignment. I suggest more steps by steps examples should be given in the videos and/or readings. That would be much easier to understand and digest. But, overall, I learnt a lot in this course. And I will spent more time to review the content in this course. THANKS.

por Migle A

27 de feb. de 2020

Great course! The lectures explain topics very well. The assignments were challenging - you might want to do a beginners Python course before enrolling into this course. I liked that assignments were focused on independent learning where you had to go online and look for the answers yourself. I believe this form of learning is the most efficient one. Great course, highly recommend!

por alex s

24 de may. de 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.

por Drew L

19 de ene. de 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.

por Rutamvar M

27 de ago. de 2020

Great course to begin with. If you find this course to your liking you can enroll for the whole specialization. The instructor is fundamentally clear and easy to understand. Some of the codes may not make sense as of now, but I am pretty sure it will make more sense later on. I felt a little more content could be added to the videos and this would be even more easier to grasp.

por Patrick L

17 de abr. de 2020

The whole course is quite demanding for me who do not need to use programming at work at all. However, it's challenging and I really feel that I have learnt something. Even the teaching staff are very helpful and the replies in the forum are very useful in completing the assignment.

The final project is a bit difficult but I hope that I could apply it in real life situation.

por Baochun L

3 de jul. de 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.

por Shawn M

25 de ago. de 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.

por Waqar A C

9 de may. de 2020

It's been a phenomenal course. Highly recommended for new comers. Instructor teaching style was marvelous . Professionalism was there. Moreover course demand reasonable analytic and programming skills to do it properly quickly with proper understanding. Learnt alot of new ways of data manupulation which i have not done before. Thank You Coursera Team for making it possible

por Martin W

27 de jul. de 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.

por Javier B

25 de ago. de 2020

Tiene cierto grado de dificultad el curso sobre todo para principiantes como fue en mi caso pero con la ayuda de los foros, repasando los videos y haciendo labor de investigación por cuenta propia y sobretodo con ayuda de Dios pude aprobar el curso y me siento muy contento y orgulloso por el logro obtenido pues el esfuerzo, tiempo y dinero invertido fue considerable.

por Linda B

4 de may. de 2020

This was a great course to learn Pandas and to feel capable of manipulating data in a Pandas Dataframe. The class was laid out very well with quality instruction and good examples in the jupyter notebook. The homeworks are where I learned the most as I really had to understand the material to complete them. I'm looking forward to the next class in the certificate.

por Julian O

15 de abr. de 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.

por Niccolo

31 de ago. de 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.