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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
13,209 ratings
1,938 reviews

About the Course

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Top reviews

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.

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.

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1476 - 1500 of 1,918 Reviews for Data Analysis with Python

By Sreelatha V

Jan 5, 2020

Very detailed and guided course that provides an overview of data analysis in Python with short assignments after each video and interesting lab courses.

By Guilherme V

Jul 3, 2020

insufficient statistic, as the name of the course is Data Analysis, i would expect more classes about the different distributions of data, pdf and pmf..

By Katarina S

Mar 22, 2020

One of the best courses in the IBM Data Science Specialisation.

I would like to have more quiz questions and opportunities to practise what was covered.

By Frank

Aug 30, 2019

I would have given it 5 stars but they barely went over polynomial regressions and pipelines and it was a major portion of the end of class assignment.

By Wenyu X

Apr 2, 2019

pros: well organized, clearly explained each step, useful

cons: frequent errors in both videos and the lab, especially on the questions part in the lab

By Maksym S

Sep 3, 2019

Final exam was too complicated. I have 2 masters degree and for me it was clear, but for other it is too complicated.

P.S. it is my personal opinion

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 Sifat 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 Randall 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 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 TooMuchSauce

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.