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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
12,030 ratings
1,739 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.

SC

May 06, 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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1601 - 1625 of 1,721 Reviews for Data Analysis with Python

By Juan S A G

Aug 21, 2020

very simple exercises which does not help to learn altough videos were exeptional

By Mohsen R

Jun 17, 2020

The course does not explain the processes enough, there should be more examples.

By Maciej L

May 16, 2019

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

By Tomasz S

Nov 19, 2018

Few small hiccups with the training videos and quite a few in the lab-excercise

By Steven B

Jun 04, 2020

Overall I felt it was not broken down very well and seemed confusing at time.

By Pierre-Antoine M

Feb 19, 2020

Videos are nice but they are mistakes in the notebooks that disturbs learning

By Toan N

Mar 27, 2020

The lab is disconnected every so often that can't complete it smoothly.

By Jessica B

Jun 14, 2019

Good content, but lots of typos. The outsourcing is extremely evident.

By Arjun S C

Aug 14, 2019

Lots of bugs and errors. No instructors reply on the discussion forum.

By Anvit S

May 13, 2020

Could have been more detailed....Important concepts just brushed thru

By Holly R

Apr 16, 2020

Could use some better mathematical description of the techniques.

By Filippo M

Sep 27, 2019

Useful course, but the IBM online platforms are not working well.

By Robert P

May 17, 2019

Some concepts were quite confusing and not that well explained.

By Atharva Y

Jan 23, 2020

As compared to other courses this course seems to be too fast

By Nirav

Jun 26, 2019

Lot's of errors in this course, please update and correct it.

By Anmol P

Oct 14, 2019

Course could have been more elaborate in depth and scenarios

By Tichaona M

Aug 05, 2020

This is a great course for building the base to use Python!

By Mia W

Dec 27, 2019

the lab is extremely useful, however, videos are too short

By Michael A D R

Nov 01, 2019

Extremely interesting BUT it gets long and hard to follow.

By Nihal N

Apr 18, 2019

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

By Alejandro A S

Jul 25, 2019

Experimented a lot of problems to complete the assignment

By Troy S

Mar 14, 2019

Quizzes are too easy. Don't even need to watch the videos

By Anurag P

Jan 18, 2020

Mostly theoretical; very little to implement on our own.

By Pulkit D

Jun 29, 2019

Please update and explain Rigid Regression a little more

By Appa R M

Oct 24, 2019

The kernal is stuck for some questions and its annoying