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

4.5
stars
25,634 ratings
5,714 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

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

YY

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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3801 - 3825 of 5,665 Reviews for Introduction to Data Science in Python

By Manikant R

May 4, 2020

Data science is itself a very broad topic, In this course, they have tried to get in touch with all basics of data science, TO BE HONEST, you will not get everything thought in this, you have to put your own hard work in it.

By Bhavya S

Apr 26, 2020

Tougher than expected. Definitely requires one to have advanced programming skills. Assignments are a level higher than what is taught in the video. Not recommended for beginners but overall one of the better MOOCs out there

By Viraj M

Apr 4, 2020

There is less focus on syntaxes which slows down the learning process as most people are still struggling with that. Other than that the course material and the instructor are very helpful. The grading system has some flaws.

By Toby P

Nov 30, 2016

Completed the course and found it pretty good for the first run. Mostly focused on the Pandas library - you'll be ok if you know a bit of Python, or have experience in another language.

Looking forward to subsequent courses.

By Gregório P d O

Jul 24, 2020

The course it's very good and I'm not giving 5 stars only because I think it is very fast paced. This could complicate the process of joining the pieces together and it's kind of a big leap from the videos to the exercises.

By suman k

May 25, 2020

This is a good course for practical hands on data in python. Good learning on map, apply, groupby, merge, data slicing, subsetting data, datetime, bin. creation

Should include datatime & cut in the assignments.

Thanks,

Suman

By Massimiliano D H

May 6, 2019

Great application of Python (really more about Pandas than Python) to data science applications. Course materials and instructors were helpful, though I do wish that the assignments were a bit clearer in their instructions.

By Leo S

Sep 1, 2017

An extremely demanding course, especially on the coding exercises. Expect long stretch of time on Stack Overflow to look up codes and examples....

I almost give up on this one, but still managed to get through after 5 days!

By Jesús C

Jun 3, 2017

Excellent introductory course to Pandas. Four stars because the pace of the videos are too fast and the assignments requires, sometimes, excesive individual learning. Hopefully the info found in the forums is very helpfull.

By Shruti M

Jun 6, 2018

You may need to brush up on some Stats concepts if you havent used them before. The assignments are sufficiently challenging, even if you have a programming background. Overall a good course to get started on Data Science.

By Jaswant G

May 24, 2020

Theory covered is minimal compared to the level of assisgnments, but i feel assignments are the best part of the course. To complete the asignments you need to explore a lot on your own and learn a lot too in the process.

By DHAVAL H R

May 23, 2020

Very good course to start with data science with python. Only thing you need is statistics background knowledge to better understand week-4 contents. But author has provided with reference to a free pdf book for the same.

By Aria B

Jun 20, 2019

The course is useful and I learned interesting techniques. It was just a bit too short in my opinion. I also think there could be more examples to show the best practices of using Numpy, SciPy, and Python in data science.

By Yash B P

May 29, 2020

This course provides a brief overview of what data science has to offer. Professor Brooks has a great command of the concept of data science. I found the course assistant a little difficult to follow with and comprehend.

By Mark H

Jan 11, 2018

The interactive python notebooks and the programming assignments are excellent. The course loses a star for the incredibly fast pacing of the lectures, and the off topic data science assignments.

Still highly recommended.

By VICTOR A

Mar 18, 2021

pretty tough even though i've been playing with Pandas in the past. But learnt many new techniques. assignments are challenging. It takes more time than what is written. I spent between 16 to 24h on each assignement...!

By Herman

Feb 28, 2020

The staffs are very good at making difficult key points clear and this is a very good course for data science starters. But the auto grader is not good, sometimes I have to debug not for my code but for the auto grader.

By Martin J

Aug 27, 2017

Good base material on data science. Not the best python course. Directions were lax during the programming and I stumbled around until I found the formulas they were looking for. Not the best direction on assignments.

By Jiao G

Jan 28, 2021

Assignments are too difficult,cause if you don't use some special functions like extract(),you will have to stack lots of iterations···but some skills and functions used in assignments are not mentioned in the lecture.

By Diana V M

Jun 29, 2019

No me pareció que fuera un curso introductorio, por el nivel de las tareas y por la explicación básica que daban de cada tema. Sin embargo, el curso me ayudó a desarrollar habilidad en manipulación de datos con Pandas.

By adeeb h

Jul 13, 2020

Everything was pretty good and the assignments were challenging enough to help increase the skills of the students opting for this course, but a bit more video lectures could be added to the fourth week of the course.

By Baswa G

Nov 22, 2017

The course content and explanation is superb, Assignments shall have access to course auditing students also though they shall not be graded, anyways thanks to Prof. Christopher Brooks to deliver such great lectures.

By Hermes M G

Oct 21, 2019

This an excellent course for people who want to refine his skilfulness using Python for data analysis with Pandas, and specially his capability of self learning from internet.

It is a kind of Learn by yourself course.

By Puleng L

Mar 7, 2018

A well structured course with an extremely helpful and responsive teaching staff. I appreciate the fact that the course encourages students to do further research on approaches to answering the assignment questions.

By Cristian C

Nov 15, 2018

Overall it is a good course, learned a lot of good things, only the overly optimistic agenda for the assignments was the problem. I had to spend much many hours than the estimated time in order to get the job done.