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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,518 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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2726 - 2750 of 2,896 Reviews for Data Analysis with Python

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 3, 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 RODOLFO C R

Jan 24, 2022

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

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 Nourhan A Y

Aug 28, 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 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 Phetole R

Jun 16, 2023

The course material did not prepare me for the final project

By Anmol P

Oct 14, 2019

Course could have been more elaborate in depth and scenarios

By Tichaona M

Aug 5, 2020

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

By 林tanya

Dec 27, 2019

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

By Michael A D R

Nov 1, 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