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Learner Reviews & Feedback for Data Analysis with Python by IBM Skills Network

4.7
stars
16,189 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Top reviews

RP

Apr 19, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

SC

May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

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1901 - 1925 of 2,446 Reviews for Data Analysis with Python

By BINAY K

Jul 6, 2019

Course is good, but in this short course it is covering lot of thing thatswhy lot of topics are just touched intead of going little bit deep into it.

By Sergio F C C

Jun 20, 2019

You learn a lot, good intro to data science with python. Labs have typos and can be confusing at times though, the only thing that could be improved.

By Aurangazeeb A K

Oct 13, 2019

A very interesting and easy course. Anyone can catch up with big concepts with little effort. Thank you Coursera and IBM for this wonderful course.

By Sucheta

Sep 2, 2019

Course is nicely designed and pare explained well.

I would have liked to see the steps along with the final answer to the peer assignment questions.

By zara c

Oct 31, 2020

Very good course. I wish there were more hands on exercises. We only had a chance to practice in one lab per module; otherwise, I learned a lot.

By Ponciano R

Feb 26, 2019

Great course to start learning python applied to analysis, but after this, I prefer to use R. Less complicated and can obtain the same results.

By Gourav K

May 31, 2022

The course material is good. However, I found the videos a bit fast and the automated audio speech is not so good. The lab sessions are great.

By S. S

May 17, 2019

I find this course useful. But some of the contents are little advanced all of a sudden and feels some important explanations are not covered.

By Venkatesh E

Jul 21, 2019

Through out the course i have learned alot like data visualisation mainly.I think i have completed successfully basics for machine learning.

By Randy G

Sep 26, 2018

I feel like this section needs some more hands on labs. Great topic over view and application. Not to much in the way of math unfortunately.

By Saurabh A

Aug 1, 2020

Good course for beginners. Can introduce little more concepts such as multi-collinearity, model accuracy etc to make it even more complete.

By Victor D S C

Jul 7, 2021

A great explanation of the concepts and methodology in data analysis , i wish we couldve gotten more peer reviews like the last excercise

By Shreyas S

Jan 31, 2020

It was a good course overall. Would prefer explanations at a slower pace and more examples for each of the techniques explained.

Thank you!

By Kunal J

Nov 14, 2019

Content : 5/5

Labs : 5/5

Final Assignment : 3/5 (It was quite easy to complete as there we instructions and code already written for you).

By Prasad T

Jan 29, 2021

need better practise questions preferably to write program instead of multiple choice answers plus needed more theory of the topics given

By Jonathan B

Jun 25, 2020

Great material. Very comprehensive. The only knock is sometimes the slides, notebooks, and quizes have typos or are not super-organized.

By Aurelio L G

Jan 17, 2020

Una visión muy amplia con acercamiento a una amplia variedad de herramientas. Faltan más ejemplos de uso, ejercicios y casos prácticos.

By Subhasish D

Jul 13, 2020

The learning are too basic, trust me in real world things are much critical. Probably coursera can help us with that kind of knowledge

By William O

Mar 27, 2020

One the greatest course of Data Analysis. The info given about statistics is very important and accurate.

Thank you to the instructors.

By Matthew A

May 12, 2019

The more advanced portions of the course felt a bit rushed without enough examples and hands-on work to really reinforce the concepts.

By Jan M v d B

Jul 24, 2021

Learned a lot about statistical analyses in this course, but the easiness of the assignment and grading quizzes make it unfulfilling.

By In W C

Oct 3, 2019

Other than some minor errors and bugs, I think this course gave good introductory material that can be supplemented with other books.

By Cindy N P P

May 10, 2020

There should be another grading method for the final task, that a system is in charge of assigning the grades, not other classmates

By Oscar C

Jan 21, 2020

The course is well designed, however, in some videos exist misspelling functions that may confuse when you try to test on your own.