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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,618 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

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.

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.

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2751 - 2775 of 2,913 Reviews for Data Analysis with Python

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

By Ghulam M

Jul 23, 2024

there is just lot's of rough discussions in my openion.

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 K S

Jan 29, 2020

It would be nice if the course had more assignments.

By Sudipta S

May 19, 2024

not that deep but I learnt a lot thanks to the team

By Bhanu S

Apr 28, 2019

It was difficult to retain the knowledge imparted.

By Alton M

Jun 8, 2019

The course requires more interactive programming.

By Xiangyu L

Jan 19, 2019

There are lots of mistakes throughout the courses