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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
17,693 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

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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2276 - 2300 of 2,715 Reviews for Data Analysis with Python

By Jeff J

Aug 27, 2019

Nicely explained. But many minor mistakes here and there though

By Bashar M

Feb 5, 2019

thank you very much ,this course was very useful and interesting

By Cherif H W A

Dec 14, 2019

as usual the labs are great but the videos could be much better

By Nicholas J F

May 3, 2019

Good content. Still spelling errors and mistakes in some place.

By Mudita N

Feb 20, 2019

Last few weeks were a bit confusing but overall a good course .

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 a

Sep 30, 2020

Buen curso, los talleres permiten la aplicación de conceptos

By Welamaza A M

Jun 18, 2022

Well taught and is challenging enough to keep one motivated

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 Duc N

Jun 17, 2023

that's an amazing course. thank you for helping a lot.

By Filiberto H

Jan 17, 2020

Very difficult if you don't have some statistics bases

By Serena 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 Takudzwa G

Jun 9, 2023

Awesome Course. The vids are rushed a little though

By Sunabh M

Apr 1, 2023

It should contain a bit more about machine learning.