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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
14,207 ratings
2,106 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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2001 - 2025 of 2,100 Reviews for Data Analysis with Python

By Xiangyu L

Jan 19, 2019

There are lots of mistakes throughout the courses

By Abdul M A

Apr 17, 2019

Not very interactive with fewer help to learners

By Ashwin G

Apr 26, 2019

Too fast and could have included more examples.

By Gerhard E

Feb 12, 2019

Copy of videos, not a fan of tools used in labs

By Yasmin A

Feb 3, 2020

Un cours riche et adéquat pour les débutants

By Hiro H

Nov 27, 2019

Very nice course. It gives you what you need

By Brian S

Mar 29, 2020

Notebooks are sloppy, with typos and errors

By Fariha M

Sep 28, 2020

The course didn't seem challenging to me.

By Sachin L

Sep 26, 2019

More examples and detailed explanation

By Nilanjana

Jul 12, 2019

More examples and code examples needed

By Hamed A

Apr 8, 2019

The course needs a final assignment!

By piyush d

Dec 6, 2019

exercises could have been better.

By Jyoti M

Mar 26, 2020

I felt it was too fast to grasp.

By Baptiste M

Nov 2, 2019

Final assignment is quite messy

By Murat A

Apr 21, 2021

could not access the labs.

By Yuanyuan J

Jan 17, 2019

Not clear on the last part

By Ahmad H

Jun 8, 2019

This course is very tough

By conan s

Dec 20, 2019

Lots of technical issues

By David V R

Jun 17, 2019

Exams should be harder

By Riddhima S

Jul 8, 2019

la lala la la laa aaa

By Daniel S

Feb 8, 2019

Not easy to follow.

By TATOU D T

Sep 27, 2021

très bon cours

By Vidya R

Apr 16, 2019

Very Math!

By James H

Apr 29, 2020

Definitely not one of my favorite courses in the Data Science Certificate series. There were times I was ready to give up the pursuit of the certificate altogether during this class... There should have been a prerequisite for this course of the statistical tools and methods that would be covered in here... Sure I could program these things after this class, but i still dont understand why I would choose to use one over another? This is one of those classes where you walk away feeling more confused than when you went in... Also there were a lot of mistakes, typos, and obsolete things in the labwork - some reported and acknowledged months ago, but still not fixed in the lab (video I can understand, but not the labs)

By Ruben W

Oct 6, 2018

The content is good, but if you are not familiar with Python, I wouldn´t recommend this course. There are a lot of typos in the video. The code contains a lot of errors where you have to find a solution. So, you are forced to debug their code often.

But if you are only interested in the course certificate, you could quickly go through the videos and quizzes, without any problems. It's easy to pass because the questions are like: What is the result of print("Hello world"). So no real challenges at all.

Please, try to fix the typos. Sometimes it was very embarrassing. Example (Week 3) instead of

"from sklearn.metrics ..." the video comes up with "from sklearn.metrixs ..."