Learner Reviews & Feedback for Data Analysis with Python by IBM
About the Course
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...
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.
UA
Jul 28, 2020
AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.
701 - 725 of 2,952 Reviews for Data Analysis with Python
By Bondili A S
•Feb 5, 2020
Awesome learning Data Analysis with Python. learned a lot and looking forward to learn more...
By Byron D
•Nov 26, 2019
The questions for the final project have some glitches (Question 3 does not accept a picture).
By Girish B
•Aug 16, 2019
The topics covered in this course are very up to date and are very industry requirement based.
By Anu P P
•Oct 31, 2021
An essential course for all those starting to learn Data Analysis, simple and understandable.
By Tomasz F
•Oct 24, 2021
The course covers very huge range of different SQL aspects.
Fully recommendation from my side.
By Akshat007 J
•Jun 23, 2020
This course gives a very quick,detailed explanation of basic techniques used in data science.
By Balaji S
•May 8, 2020
Although some concepts were quite deep, the author made it appear simple and gave confidence.
By Prakash G
•Apr 28, 2020
Good explanation about creating and evaluating model. Looking forward to have more challenges
By Adeel T
•Apr 2, 2020
Excellent Course.
If you are new to python and data analysis. This is for you.
Very well done!
By Kumar S
•Aug 12, 2019
Great Course.Very insightful. Although, there should have been more partice and test sessions
By Vishal R H
•Jul 13, 2021
Thanks a lot Coursera and IBM for this learning opportunity and knowledge add on in my list.
By Shivakumar K H
•May 2, 2020
Very good course. I have found it very informative and fun learning statistics with python:)
By Tomasz P
•May 29, 2019
Very interesting! Good explanation of the concepts. Interesting examples and visualizations.
By Bakyt N
•Feb 15, 2019
Very useful. Probably the most useful in the series (Professional Data Science Certificate)
By Andres T
•Feb 2, 2025
Excelente, el proyecto me pareció genial y permitió probar todas las habilidades aprendidas
By Breyner P
•Oct 26, 2024
This is a great introductory course to the topic of data analysis. It is well worth taking!
By Ahmed E H
•Feb 29, 2024
I enjoyed this course, it's one of the best courses in the IBM Data Science specialization.
By Abhishek S D
•Jan 27, 2024
Lectures are on point. A very good course on data analysis with python. highly recommended.
By Min W
•Feb 20, 2022
A good course for beginning learner, the design of videos and practices is pretty friendly.
By Fatih A
•Dec 24, 2020
It was very good and also a little bit hard but really delightful course. Thanks a lot IBM!
By Adefolu A
•Nov 26, 2020
Well package course. Thanks to IBM and Coursera for enriching my knowledge on data science.
By Madhu G
•Jun 19, 2020
This is the great course for learning data wrangling, data visualization and data analysis.
By Asset A ( s k
•Apr 18, 2020
This course was perfectly suited to me, all tasks and instructions were clear and accurate!
By Jack C
•Apr 2, 2020
This course really helped me understand regressions and linear transformations with python.
By Tetiana R
•Jan 21, 2025
A really useful material, well organized, and easy to digest. Thanks a lot to the authors!