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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,616 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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2351 - 2375 of 2,912 Reviews for Data Analysis with Python

By Collin C

Jan 6, 2020

Well organized topics with pretty sufficient instruction. The more advanced coding only got a cursory explanation.

By Marco S S

Nov 9, 2020

Very good course, it goes straight into the useful tools and concepts in regards to data analysis and prediction.

By Juan L S

Nov 20, 2018

I mean, it's super well prepared, but the scalation of topics seemd to be a it too quick, at least it was for me.

By Amit K S

Jun 27, 2020

The videos are bit faster. It would have been better if it was done by some real teacher rather than voice over.

By Harjit S G

Oct 25, 2019

use of names was a bit confusing at times compared to final assignment, but otherwise very helpful and enjoyable

By Jeremy G

Oct 12, 2020

This course should come after the Data Visualization with Python course in the Professional Certificate program

By Lida X

Jan 10, 2020

Maybe a bit too fast for those who are not familiar with various kinds of regressions...

Other parts are great!

By Cristina

May 29, 2018

Interesting course, but there are some moments when they give an interesting idea, but not the implementation.

By CAMILO A P Q

Jun 20, 2020

Good course, but it's too basic. I learned basics of pandas, scikitlearn, seaborn and other python libraries.

By Nikhil

May 14, 2020

High quality, concise content, well timed videos with pop up questions that ensures focus of the participant.

By Deepak P

May 18, 2019

The Content was really good but some topics are explained in very short.

But Thanks for this awesome course!

By Kerem B

Feb 3, 2020

The difficulty level of this course goes up very dramatically and it took me very long time to understand.

By Gabriel A

Jun 6, 2019

Best course in the specialization so far. An introduction to the statistical concepts could be beneficial.

By Praveen

Jul 20, 2019

Very good introduction to data analysis. Some of the concepts mentioned here needs much more explanation.

By Mr. S

May 1, 2023

Really good course, just that sometimes it seems it takes in big steps which may provoke some confusion.

By FILPE R F

May 29, 2022

It was a good course. However, in my point wiew, it was necesserary exploring the Pandas and Numpy more.

By Jonathan P d A

Nov 6, 2018

Great course with great classes. The exercises are not complex which makes the practical part less good.

By Lucian P

Dec 13, 2021

Great content but problematic when you need to use IBM Cloud platform that doesn't accept new accounts.

By Juan J F

Mar 22, 2021

An excellent introduction to the techniques to analyze data and do the validation, very clear exercises

By Venna R D

Feb 2, 2024

A very good and detailed explanation. A little bit of assistance in coding should improve in the labs.

By Akshay S

Jun 22, 2020

Overall coerce is good. Just the algorithm explained at last weeks need to be more simple explanation,

By Rajeev P

Mar 22, 2020

It was a good course. Learnt a lot of statistics and how to implement them in python from this course.

By Hung C T

May 1, 2019

Would be better if some underlying theory of advanced topics is covered, such as Ridge Regression etc.

By Nicholas F

Nov 24, 2020

It would be good if there were more practice opportunities. Overall a good class for familiarization.

By SHALIN S

Sep 16, 2020

week5-6 labs were tough for writing own code and for understanding. However for awareness, it was OK.