Chevron Left
Back to Data Analysis with Python

Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,446 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.

Filter by:

251 - 275 of 2,884 Reviews for Data Analysis with Python

By Saurabh M

Aug 31, 2020

Its very nicely designed course .Its designed such that you get brush up your fundamentals and get to know the real taste of statistics and probability applying practically to real world. i really enjoyed and earned a valuable knowledge.

By Ricardo S

Feb 24, 2020

La calidad de los cursos de coursera es excelente. Obviamente tienen detalles que se deben trabajar como algunas presentaciones que no coinciden con las voces en off. Sin embargo con suspicacia se pueden solventar estos infimos detalles.

By Krishnamurthy A

Nov 13, 2022

I applied for financial aid and got approved with the same.I am yet to start with the course but am getting the message assignment overdue.Kindly push the dates so that I will be able to complete the courses and assignments comfortably

By Ritik K

Jul 2, 2020

I learnt a lot in this course, the teaching way is quite good with animation and real life based example. I must say the course is designed very carefully. I want to thanks all the course creators to gave us such a great opportunity..

By Jafed E G

Jul 6, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

By Mahdi G

Jun 14, 2023

Really it is Worthfull Course. Helpfull Training Method. Nice Videos & Specially The Labs Are Worthfull & Helpfull.

I extend my thanks and gratitude To Coursera & IBM To give me chance learning. i Say Best Wishes & Regards. u r great

By V.S.S. T

May 15, 2020

Very helpful and useful course especially for beginners who are willing to gain knowledge on Data Analysis. I would recommend starting with this course for those who are interested in mastering their skills in Data Science later on.

By Richard M

Jul 10, 2023

El curso hace na revisión a nivel básico de aspectos que te conducen a la realización del análisis de datos, utilizando comandos no solo de librerías de Python como Pandas, sino tambien de conceptos fundamentales de estadística.

By Zwanga R

Jan 27, 2022

The course was very interesting and exciting. The videos were well presented and laid out in a way that is easy to follow and eager to learn follow. Assignments and exercises made us quite interactive and I really enjoyed that.

By Sayak P

May 13, 2020

This course is based mostly on very basic concepts , it's good for those lacking the slightest knowledge in the field of statistics , but yes for beginners it's pretty fine.I loved the presentation of those labs,quite useful

By Daniela V

Nov 3, 2022

Excelente curso. Con ejercicios prácticos y un nivel más experto de Python explorando otras librerías mas complejas y con mayor aplicación en machine learning y estadística. La metodología del curso es muy dinámica y amena.

By Phil L

May 31, 2020

Really good course. More challenging than I expected. I expect it will take a few applications of the concepts to get them down 100%. Very good presentation of material. The labs were critical to learning the concepts.

By QUAN Z

Feb 25, 2019

The course perfectly fits those who has some knowledge on python and want to do data analysis with it. It explains how professionals would process data, build model with the data, and use the model to solve a real problem.

By Bhargav M

Sep 14, 2024

Good course. Gives you the skills you need to analyze data with python. I had to spend even more time because I straight up took this course without much idea of statistics and I wanted to really understand the concepts.

By Min T A

Mar 18, 2021

This course covers exploratory data analysis and even furthers onto machine learning with some key statistical introduction such as Linear Regression, Correlation, P-value, F-score, etc, explained in its most clear form.

By K58 L D Q

Sep 25, 2021

A very interesting and informative course. I have access to the foundational knowledge in using Python for Data Analysis. The labs are helpful as well. I know I can apply the lesson I've learned in real life, real work.

By Pranav K J

May 10, 2020

Very good course and well designed , so that a new person also can understand it very well. They way it is taught is admirable. I will recommend, the aspiring data science Engineer, must take this course specialisation!

By Jonathan I O

Jul 14, 2019

This course provides a robust walk-through in the use of python for data analysis. The labs ensure the theories taught are put into practice through hands-on projects that further reinforces skills learned. I loved it!

By Aman S

Mar 26, 2020

A very detailed course. The hands-on exercises were really good and I got to learn a lot of things from this wonderful course. Thanks to all the instructors for their hard work in putting together such a course for us.

By Yan Y L

Aug 28, 2022

The course structure is clear. I can recall the concepts learnt in the previous chapters on this course.

The Final Assignment rubic is clear. I know what I should hand in to prevent mark loss due to misunderstanding.

By Katja K

May 25, 2022

Really helpful course to learn the basics of pandas and scikit-learn. The videos were easy to follow and very clear, and they were complemented well with the lab notebooks and quizzes. Thank you to the organizers! :)

By hamidreza m

Sep 29, 2022

As a data scientist in retail industy I recommend this course to you because this course has lots of meaningful topics and educated professors are teaching you.

Hope you the bests and enjoy learning with Coursera!

By Paul A

Sep 24, 2020

I think this course is the highlight of the Applied Data Science specialization. I learned so much and gave me the tools to learn more on my own. It was really engaging and I never had a dull moment in this Course.

By Roseline A

Jul 9, 2020

This is a great course. I went away with so much knowledge on modelling and model testing. The labs are also very well structured and not just a repetition of the class presentation. I recommend this course highly.

By Ferenc F P

Feb 26, 2019

The beginning of the course helps you understanding how you can manage your data with python. In the end linear regression, and ridge regression is also introduced. Good course for those not familiar in this field.