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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
19,407 ratings

About the Course

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement....

Top reviews

RM

Jun 10, 2020

Great course to learn the basics for Data Analytics using Python.I really liked the framework and data analysis template or process given in the labs. I will use them as a reference for my real job!

ND

Jul 31, 2021

T​otally overwhelmed with the course contents and easyness in teaching. The course will make you familiarize the fundamentals in a way that you will never forget when you used in a real world.

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2876 - 2900 of 3,070 Reviews for Data Analysis with Python

By Miguel A I B

May 14, 2020

Exelent training to get familiar and intruducing to Python capabilities and programing

By Xinyi W

Jan 26, 2020

Superfacial level of Python while being not very through on the data analysis methods.

By Ana C H

Jun 12, 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course

By Sathiya P

Aug 27, 2019

Nicely thought, but I felt concepts like Decision trees, Random forest were missing

By Ros R

Aug 13, 2019

The course is too long. The material should be divided and explained more detailed.

By Amanda A

Apr 17, 2020

There were many typos in the labs which made it difficult to understand at points.

By Juan S A G

Aug 21, 2020

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

By Naresh T

Aug 12, 2023

It's really good course i really enjoyed learning new things in data analaytics.

By Naf

Nov 2, 2022

It was a good course but maybe a little too easy with all the prompts provided.

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 20, 2018

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

By Craig S M

Mar 21, 2022

It ok. Some parts of the course were bare bone. I liked the hands on sections.

By Steven B

Jun 4, 2020

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

By Pierre-Antoine M

Feb 20, 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 RODOLFO C R

Jan 25, 2022

This course focus on very important subjects but in a sketchy aproach

By Arjun S C

Aug 15, 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 Nourhan A Y

Aug 29, 2024

This course needed to be updated it lacks a lot of important basics

By Dibyendu M

May 20, 2023

The practical lab having technical issue .PDF is not downloadable.

By Holly R

Apr 17, 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.