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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
12,075 ratings
1,746 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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1626 - 1650 of 1,726 Reviews for Data Analysis with Python

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

By Qing L

Jan 26, 2020

Kurs gut organisiert aber

die Fragen sehr oberflächlich

By Jakubina K

Dec 19, 2018

It would be more useful if labs were be rated as well.

By Ankit S

Jan 29, 2020

It would be nice if the course had more assignments.

By Bhanu S

Apr 28, 2019

It was difficult to retain the knowledge imparted.

By Alton M

Jun 08, 2019

The course requires more interactive programming.

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 ABOUDA Y

Feb 03, 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 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 09, 2019

The course needs a final assignment!

By piyush d

Dec 06, 2019

exercises could have been better.

By Jyoti M

Mar 26, 2020

I felt it was too fast to grasp.

By Baptiste M

Nov 02, 2019

Final assignment is quite messy

By Yuanyuan J

Jan 18, 2019

Not clear on the last part

By Ahmad H

Jun 08, 2019

This course is very tough