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

25,768 ratings
5,734 reviews

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


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


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.

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3676 - 3700 of 5,687 Reviews for Introduction to Data Science in Python

By Marc M M

Nov 28, 2017

course is very good to learn the python basic pandas, numpy libraries.

I would prefer to have a reference book associated to the course so we reference to it, it will be great for future while coming back and read what we learned.

The grading system consumed most of my time to make sure to have my answer graded correctly.

By Pineapple P

Aug 21, 2018

It's a great course and during the process I learned a lot about python pandas applied to data processing. The only downside I see is that the lectures does not prepare you well enough for the homework at the end of each week. I had to spend tons of time googling about pandas in order to finish the homework each week.

By Wallace T

Aug 7, 2018

The auto-grader is sometimes frustrating. I know the course staff is providing the code to let learners to find the errors, but it's in the forum and I only know it after several rounds of frustrations.

Please mark those checking codes in the question too! It helps provide a happy learning experience to every learner!

By Vitor C

Nov 4, 2017

Course is well structured. Most of the concepts are given quite quickly in the video lessons which is good since each learn is free to decide whether she/he wants to do further research in a specific content. Assignments are quite difficult and consume more time then estimated, but you actually get to learn the thing.

By 宸宇 田

Jan 30, 2018

this is my first course in Cousera, and i am a novice in Python. I think this course is really impressive. I learned how to use Python to process data quickly. I really recommend this course if you are interested in Python and Data Science. I decide to learn the machine learning course next, I love doc.Christopher!

By Sathya K

Aug 24, 2017

I like this course very much. I would rename the topic like data manipulation using python. It is definitely not just an introduction program to Data science. The questions are very challenging especially from week 3. But, I am very confident on taking any problems for data science to manipulate it successfully.

By Venkatesan K

Dec 14, 2019

The assignments were really interesting and challenging. But the lectures could have explained the syntax a bit more clearer. I was forced to look at the documentation for every single line of code during the lecture. The pace should be reduced. Otherwise its really a good course and you can really learn a lot.

By Rohan C

Apr 22, 2022

In the begining, there were practice questions at the end of each video. As I progressed, I obseved that only assignments are there. I would request you to provide more questions so that we could better insights and get more hands-on experience. It will help us to build strong problem-solving skills.

Thank You.

By Joan P M

Jan 17, 2022

B​uen curso para acabar de apuntalar los conocimientos en Pandas y lectura de datos. Hace falta un conocimiento previo de dicha librería. La introducción de Regex es de vital importancia para este curso. No le doy 5 estrellas porque hay muchos momentos donde se tira demasiado de Google para acabar las tareas.

By Harsh J

Apr 18, 2020

Great course. Well explained, and the assignments challenge and push you to explore by yourself. Sometimes however the system that reviews your assignment can be frustrating as it expects the output of your answers in a particular format/way. I guess but that forces you to modify your code in that manner to.

By J

Apr 27, 2017

Content was generally well covered. One improvement could have been slightly better examples of how there are multiple different ways to solve the same problems; the instructor would often allude to this but would just advise the student to read through the pandas docs, which could be non-intuitive at times.


Jan 9, 2021

El ejercicio de programación de la semana 4 de la sección 1, donde se hace trabajar con datos de estados, ciudades y equipos de deportes, me parece poco útil, demasiado manual y muy lento. Considero que es un muy mal ejercicio. Todos los demás estuvieron muy acorde a los problemas y la materia que se enseña.

By Haining Z

Apr 16, 2020

I learned a lot, but the assignments really could have been explain better. It was not clear to me what type of format/output I should give at multiple times. What I did was keep submitting while adjusting the output until it was right. A hypothetical screenshot showing what the result looks like would help.

By Joshua Z

May 29, 2017

Good course; a great intro to relevant concepts with guidance towards realistic tasks. Only negative is that sometimes problems are unclear (maybe its just me) and spent too much time trying to get outputs exactly right to pass auto-grader. Good experience, and I plan on continuing with the specialization.

By Monika D

Jun 12, 2020

I liked assignments they actually helped me to learn.Also book - Python for Data Analysis , 2nd Edition - Wes McKinney was great learning. I would just like to add in that if the videos can have better course material for Week3 and Week4 as assignments were bit higher level than what was included in videos.

By Harsh B

Sep 28, 2019

This course was nicely curated. I learned about the Python lambda functions,dates ant time,objects and map() in week 1.In week 2 and 3 I learned about pandas.In week 4 I learned about the distribution and Hypothesis testing in Python.In video quizzes cleared the doubts regarding fundamentals of the topic.

By Kamruzzaman T

May 31, 2020

One of the best courses along with a highly capable instructor. Very helpful teaching stuff and discussion forums. However, an assignment asked for the mean of a value but produced wrong answer for mean and showed right answer for sum. This needs to be reviewed. Also, many assignments need better clarity.

By Srinivas R

Oct 9, 2017

very good introductory course though with a steep outside the lectures learning curve. good for you as that is how much of learning takes place, not only through some one pointing the way but having a destination (hw, assignments etc) and finding your way to that goal along with others (discussion forums)

By Sam M

May 7, 2020

Good class and the topics covered are great. Challenging and useful. The lectures are a little light on detailed information and some text or deeper/more detailed lectures would make this perfect. You will spend a lot of time looking for things to support what you learn to really get an understanding.

By Kevin D

Apr 9, 2020

Videos are great and easy to learn. Forums are great and help with guidance. Improvements would be: better ways to debug your code and more importantly your results. Your code may get results but its not clear what is incorrect on them. Overall UofM produces some of the best work. Great professors!

By abdelrahman a

Oct 19, 2020

one of the hardest deadlines I ever did, missing some more hints for where the error is,

but really powerful makes you think in different ways as if you a real data scientist, I liked it

and I recommend it even if you were old in the field of data science, this course will really

make you try your best.

By Himanshu C K

Jul 7, 2019

I commend the quality of the course and am very thankful to the instructors for developing the contents of the course.

My only suggestion would be to align the lectures better to suit the level of the assignments so that people who don't have a strong programming background can keep up with the course.

By Vedant S J

Apr 24, 2020

The course was brilliant. It tried to cover a lot of aspects in a short span. The only thing that was not good was lack of explanation of the datasets & tasks provided in the assignment. Clarity in the expected output was not there as a result of which correct assignment submission became difficult.

By Ploy W

Aug 17, 2019

The course poses itself as a good brief introduction to make you more comfortable at approaching data science project. Recommended time would be 1-2 weeks. However, point deduced for the hassle with auto grader! I also hope that the project could involve people Skyping or collaborating in some way!

By Silvestre N F

Feb 27, 2017

Not for beginners.

Level of difficulty increase very fast.

You need to dig external reference sites and use discussion forums in order to figure out some assignments requirements.

Overall quality is very good.

Should have some better tips and validation scripts in order to help debugging assignments.