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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
13,194 ratings
1,937 reviews

About the Course

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

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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1526 - 1550 of 1,917 Reviews for Data Analysis with Python

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 Arhiliuc C

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 Jesús G A S

Jun 6, 2019

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

By Angam P

Jul 20, 2019

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

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 Juan J F

Mar 22, 2021

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

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 Henry, H 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.

By Viwan J

May 24, 2019

It is a good course but -1 star because many typos/errors/unclear tasks in the assignment submission.

By Vicente C L F

Nov 18, 2019

Very good course! I just missed more deep content as optional reading in Ridge, Grids and Pipelines.

By Juan D M G

Jun 17, 2020

Muy buen curso y muy buenos laboratorios! SIn embargo a veces no explican la teoría tan al detalle.

By Shrinidhi S

May 9, 2020

My assignments with the correct answers were only given partial marks.Pls do the need for the same.

By Daniel O V

May 6, 2020

I think it should have a higher level of difficulty, not so much more difficult but a little more.

By Fab T

Jan 30, 2019

Great! Still thinking in go back to review the details that maybe I missed.. But excellent course.