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

4.5
stars
26,484 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

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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3851 - 3875 of 5,804 Reviews for Introduction to Data Science in Python

By Carlos A R R

Jul 5, 2017

Very good course with a lot of material and challenging assignments. Gave it only 4 stars because in some assignments is more difficult to agree with the autograder than to get the correct answer (e.g., data type mismatch between float and float64).

By Shailesh K

Sep 9, 2021

Excellent explanatory videos and lot is covered in just four week of course but it definitely need good grasp of pandas and numpy libraries for passing the assignnments. I definitely recommend this course as it will push you to learn and do more.

By Abhishek R

Mar 16, 2018

The content is really not good for novices. But the challenges I faced during assessments, did a lot of help. I can now understand the topics much better and at the least I am able to plan to clean the data and work on it much better than earlier.

By Nitesh R S

Mar 21, 2017

The course content is great. However, basic knowledge of python programming language is required. Since I didn't know python coding rules, I really struggled for a while. Maybe, basics of python in additional resources will help a lot of learners.

By Ahmad S

Oct 21, 2018

In my view, It is recommended to study a book on Python data analysis tool-kit panda and numpy. The course video quality is very good, instructor voice is clear and load. I highly recommended to take this course who wants to be a Data Scientist.

By vineeth s

Aug 4, 2018

This course would be recommended for anyone who has got good python skills already and want to do data analysis using python at a quick pace. Overall, It is fun doing the assignments and thinking more in a pandas way rather than in pythonic way.

By vishal r

May 5, 2020

The projects were extremely helpful to learn various concepts . The videos could have been a little more descriptive to equip us with a little more knowledge so as to tackle the projects with a little ease .apart from that it was really great

By Lee A

Jan 15, 2019

Class was good, and the information was presented in a way that was straightforward to understand and apply. I wish the exercise autograder provided more feedback. Sometimes the lack of actionable information made it difficult to solve problems.

By wondertweet

Apr 16, 2018

The course is a good introduction for data science and helps me learn pandas and numpy. You may not learn how to use these tools only form this online lesson, but you can be aware of what you need to know if you would like to work on this field.

By MONIKA C

Dec 28, 2019

Good, comprehensive course. At the end you are ready to get and clean data and make some simple analysis on your own. But you need a lot of effort to do programming assignments. Save double amount of time than it is estimated for this course.

By Xiaojie Z

Nov 26, 2018

This course provides good material. The assignments could be very difficult because the instructions were not clear. In real life, you would have a chance to clarify while it is difficult to do so in coursera.

Overall, it is a good course.

By Darren S

Nov 21, 2016

The course was great - the lectures were clear and simple; I learned a great deal! However, instructions for the assessments could have been clearer, and there were a few issues with the autograder (though I'm sure those will be weeded out).

By Richard B

Aug 21, 2018

Generally good - with challenging assignments, explanation could be better and grading unit tests more flexible.

Some of the content is rushed - but it is comprehensive and you need to have some python programming behind you before you start.

By Remo L

Mar 2, 2019

it's a good, but challenging course as Introduction to Data Science. It will require the student to read pandas documentation and/or search for help on Stack Overflow. If you're stuck, there is usually good help on the course forums though.

By Qian H

Jun 25, 2017

Nice course but the assignment is too hard for the beginner, and the assignment and the course materials are not match enough. We have to do a lot self-study when doing the homework. But the skills I learnt from the course is really useful.

By Matt M C

May 3, 2017

This course worked better as a guide than it did as a course. I learned very little from the lectures and had to do most of my learning on my own. One of the assignment even explicitly told students they would have to go learn on their own.

By Jeffrey L

Sep 2, 2018

Pretty descent course, however it felt like most of the course consisted of the assignments and self-learning rather than instruction. That's probably ok given the content was more oriented around tools and less around concepts and ideas.

By grant

Sep 15, 2019

most of this course is really great. but I do think the assignment doesn't match the course very well. To finish the programming assignment, I have to go through a lot of materials and documentations. I hope the teacher could cover more.

By Muhammad M A

Sep 17, 2020

Excellent course to get you started with dealing with data. You'll learn a lot about Python, Numpy, and Pandas, and the best part is that you'll get your hands dirty dealing with real-world data and you'll also solve real-world problems

By Jhoan S G S

Jun 28, 2020

Muy buen curso, sin embargo deberían actualizar la versión de pandas y demás librerías en los libretas y assigments.

Very good course, however they should update the version of pandas and other libraries in the notebooks and assigments.

By Charles Z

Sep 21, 2019

Good contents, but very poor grading system. Had to guess what was expected. For instance, get_list_of_university_towns (week 4 assignment), I set the indexes on both columns, which led to failure. After I removed the index, it passed.

By Trevor A

Jun 5, 2017

Great introductory course on data science in python. However, the final projects diverts significantly from the course material, requiring vast amounts of self-study for someone new to Python. Definitely learned a lot in this course.

By Michal M

Dec 19, 2016

This was a good course and quite challenging. It requires a lot of self learning if you are not familiar with pandas. I wish some of the technics that were required to solve the assignments were better explained in the course material.

By Philipp H

Mar 1, 2017

This python is mostly an introduction to the Python Pandas API. It teaches everything by example, but at very fast pace, and the videos are really just preparations for the assignments, which can easily take more time than specified.

By Enes U

Jul 26, 2020

Very good course, analysing very important Python tools to be able to create data science projects using python, course and videos were a little bit fast for me especially when i trying to understand native speak of the professor.