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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.6
6,526 ratings
809 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

RP

Apr 20, 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.

OA

Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

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701 - 725 of 804 Reviews for Data Analysis with Python

By Guillermo M M

Aug 20, 2018

It is missing a last project like in the two other courses... It would have been quite fun to be able to apply what we learnt in a project.

By Raghav N

Sep 14, 2018

This course is definitely very helpful to people who are passionate about Data science and have basic to intermediate understanding of Python but this course can be much better if it includes coding assignments rather than quiz submission. It was a great experience.

By Toan T L

Oct 23, 2018

Decent videos on Data Analysis techniques.

But the labs are poorly constructed: typos, inconstant question and solution, un-commented code and under-explained lab result.

It's a shame since the labs in other courses in this series are very high-quality.

By Raj K

Jul 06, 2018

It would be great course for beginner to have idea about different steps involve in data science job. I would recommend to go with this course. I just took 3 days to complete this course and you can do in 2 days also. Depending on your speed.

By Vidya R

Apr 16, 2019

Very Math!

By Teofilo E d A e S

Apr 16, 2019

Too complex for easy understand. Should have some documentation explaining the process and comparing the new methods.

By Abdul M A

Apr 17, 2019

Not very interactive with fewer help to learners

By Dylan H

Apr 03, 2019

While a bit fast and loose with the concepts, does contain a lot of practical code as to how exactly to bring things discussed about, which is appreciated.

By Nihal N

Apr 18, 2019

not in depth.... needs more clarity on a variety of topics

By Benoit P D

May 04, 2019

The content of the course is very interesting. There are lots of typos in the lab workbooks though. Additionally, i found having to use Watson Studio for the assignment / labs as opposed to plain Jupyter a little annoying.

By Ivan L

Apr 29, 2019

Typos are very unprofessional and spoil impressions of the course. Tests and labs are super-easy and do not make you think, and you only need to repeat commands from the lectures.

By Bhanu S

Apr 28, 2019

It was difficult to retain the knowledge imparted.

By Debra C

Mar 24, 2019

Course was worthwhile for general understanding of what can be accomplished with Python.

By Hamed A

Apr 09, 2019

The course needs a final assignment!

By Sadanand U

Apr 09, 2019

It would be great if we go in a little more details of when to use which metrics for evaluation. Instead of running through a bunch of concepts you could have spent a little more time in each of them.

By Chioma J E

Apr 10, 2019

The course was not detailed enough. I think the instructor assumed that people taking the course would know a lot about Regression, Correlation and some other statistical functions, that it was hard to understand or follow at times. Maybe consider 'dumbing' down down the statistical functions so that newbies can also follow.

Overall interesting course. Thank you.

By Nadeesha J S

Apr 11, 2019

I would like to see a final project in this course. It will encourage the learners to do more work.

By Robert P

May 17, 2019

Some concepts were quite confusing and not that well explained.

By Maciej L

May 16, 2019

Too many complicated things happening at once. It is hard to digest and follow.

By BT

May 28, 2019

Lots of good concepts. However, too complicated and could have been explained a bit more.

By Jesse Z

Jun 05, 2019

For such a important topic, it seems like the videos sped through some essential topics.

By Jackson V

Jun 06, 2019

Not as impressed with this course as the previous courses. My main complaints were:

-Seemed to be some gaps between the lectures and labs

-Some lectures seemed rushed through w/ simple questions, and did not prepare well for the lab

-Pre-written code in labs would produce errors

-Spelling mistakes (i.e. the week 5 "Quizz")

-No final project to conclude and summarize up our learning

By Alton M

Jun 08, 2019

The course requires more interactive programming.

By Ahmad H

Jun 08, 2019

This course is very tough

By Ana C

Jun 11, 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course