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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
13,203 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

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.

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.

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1601 - 1625 of 1,918 Reviews for Data Analysis with Python

By Ismayil J

Nov 5, 2018

Good overview of classic Statistic methods performed in Python.

By Shine

Jun 18, 2019

There are something wrong in the final assignment submit page.

By Tatiana K

Jan 25, 2019

Great course, but the number of errors in videos is tremendous

By Yongda F

Jun 16, 2020

This is a good course for beginners, but not enough in-depth.

By Eliezer A

Jul 30, 2019

there are some errors in the code lines through the lecutres.

By WANG T

Jan 24, 2019

Typos in the videos and notebooks should have been corrected.

By Raja U A

Mar 4, 2021

Course Contents were excellent but not well arranged/planned

By Alvaro H A C

Sep 30, 2020

Buen curso, los talleres permiten la aplicación de conceptos

By Abhay S

May 12, 2020

Quiz sections are very simple in comparison to the lessons.

By Brijesh O

May 6, 2020

Final assignment could be better thought out. very simple.

By Rahul S

Jul 18, 2019

Very Helpful course..and very good contents..learnt alot..

By Narayanaswamy N

May 25, 2019

First go for module 8 - Machine Learning and come to this.

By Ajay M

Mar 7, 2020

The Non-Graded Online Assignment need more practice cases

By Filiberto H

Jan 17, 2020

Very difficult if you don't have some statistics bases

By Serena R T

Nov 22, 2019

A tough course yet interesting. Like the lab exercises

By Ran D

Jan 4, 2019

The question jumped up in the video is quite annoying.

By Umasankar M

Aug 1, 2020

Need more model development examples will be helpful

By Themba M

Jun 11, 2020

Explanation of lab steps has a room for improvement.

By Andres E S G

Jan 11, 2020

It could have a little more theory about statistics.

By Adesua A D

Nov 4, 2019

My first course on coursera and its very informative

By Alexandru S

Jun 3, 2019

A lot of information, it is at times hard to follow.

By Boru R

Sep 6, 2020

good course, but final assignment is way too simple

By Siu T J

Jul 19, 2020

Week 4 was too hard, while other modules were okay.

By Pham T S

Jun 13, 2020

Very good course for learning about buidling models

By Neelam S

Jan 3, 2020

Examples should contain more codes used frequently.