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Learner Reviews & Feedback for Introduction to Data Science in Python by University of Michigan

4.5
stars
26,897 ratings

About the Course

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....

Top reviews

YH

Sep 28, 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.

PK

May 9, 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

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4201 - 4225 of 5,915 Reviews for Introduction to Data Science in Python

By Jorge E

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Oct 16, 2020

Buen curso introductorio con Pandas. Me sirvio para conocer la forma de limpieza de fuentes de datos y su union para luego hacer calculos estadisticos

By Ahmed A E

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Sep 24, 2020

it was very exciting but so fast and requires a good background in Python. I think it is not suitable for people from for example C or C++ background.

By Rajput S

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Jul 16, 2020

I think the course Assignment is difficult and the course theory is not up to assignment level, I found difficulty in solving nearly every assignment.

By Joe P

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Feb 19, 2018

Good overview of fundamentals. Could do with more information on last few parts that feature quite heavily in the assessment (e.g. statistical tests).

By Subbaiah M A

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May 7, 2020

Gave me an insight of how Data Cleansing, Eliminating Noises and running Statistical Analysis can be done and it gave me an exposure to Data Science.

By Vishal S

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Dec 16, 2017

This course is much more useful for someone who wants to get a touch of data science but one should have some basics knowledge of python programming.

By Sandip K D

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May 2, 2020

Great Course. The assignments are challenging and this gives you an idea of how difficult it is to clean and perform calculations on real life data.

By Jun X

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Nov 17, 2019

The submission of last assignment is troubsome due to system design. Takes time to solve it. But it gave me a lesson how should I write robust codes

By eric g

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Jan 9, 2017

Requires most projects to be completed without the videos help. Need to research and find answers elsewhere. Also need to have good sense of python.

By Yuhuan Z

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Jan 30, 2020

Very challenging course. But you can really learn something by solving challenges, right? It depends on how much you want to learn from the course.

By Chris P

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Dec 20, 2018

Very good course. This was probably a little too advanced for me but that's because I jumped too far ahead in my educational journey. Good content!

By Jeremy K

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Aug 20, 2017

The videos should prepare newer Python learners better to complete the assignments. Moreover, some questions are very vague and unnecessarily long.

By Abhijit D

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May 31, 2020

The course gives me an overview of Data science and Data visualization. However more explanation on the statistical topics would be more helpful .

By Haldankar S N

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May 3, 2020

Overall this is good introductory course but the assignment questions should be more clear, as there are lots of doubts at each step of assignment

By Naveen K

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Jan 17, 2019

Please improve the autograder .Its annoying to be not graded for correct answers. Otherwise the course is perfect. Loved it !! Thank you very much

By Phil L

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May 13, 2020

A great course with challenging exercises. The tutorials could provide better guidance on concepts that you need to take with into the exercises.

By Alan M

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Mar 24, 2020

Sometimes I had problems understanding the instructions in the exercises (e.g., definition of start of recession). Otherwise, Everything is good.

By Ravneet K

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Aug 25, 2018

the questions of assignments could have been framed in a better way. Some questions are very confusing and even the forum doesn't help all times.

By Harsh G

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Jun 3, 2020

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

By Jatin R

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May 16, 2020

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.

By Víctor A M G

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Jan 27, 2020

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

By Amol V B

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Jan 7, 2019

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

By Saivijaay V K

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Oct 12, 2022

The assignments were amazing to get the practical values but more statistical content is need to get the idea of chi-square, anova tests etc.,

By augustus e

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May 11, 2020

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

By Wynona R N

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May 7, 2020

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.