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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,518 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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2676 - 2700 of 2,896 Reviews for Data Analysis with Python

By Neo B

Feb 11, 2019

Data visualization was taught in details in course 7 and regression was taught in course 8. With no backgrounds, the codes in this course are scaring pe

By Goh S T

Apr 8, 2020

The section on model development and evaluation is not so clear. It is difficult to understand if you have no prior knowledge of machine learning.

By Girgis F

Dec 31, 2018

Course was great however i felt a lot of material was covered in a short period of time, this course can be 2 or 3 courses based on the content

By Guillermo M

Aug 20, 2018

It is missing a last project like in the two other courses... It would have been quite fun to be able to apply what we learnt in a project.

By Alexander P

Jun 14, 2019

Lots of spelling and grammatical errors that made it difficult to understand some of the material. It is otherwise an interesting course.

By 靳文彬

Mar 11, 2020

There is no slides to download or review after class which makes it hard to go over the knowledge again without watching the video again

By Siwei L

Jan 23, 2020

The video is too short and many concepts remain unclear or poorly explained. More contents need to be added to the questions and tests.

By Mila M

Sep 8, 2024

the videos were automatic and very fast paced; real person video instructors make for far more engaging content and better learning

By Carlos G R G d l C

Mar 26, 2020

It's an excellent course; the best part is the labs. It's a pity that we (the students) have a lot of problems loading the labs.

By Pedro F

Aug 22, 2019

Little bit confusing, unstructured and not easy to follow. Material inside is good though, but the course needs to be improved.

By sangeet a

Apr 8, 2020

Things are too fast in this course and many things remain unexplained which makes it difficult for one to understand properly

By Dominic M L C L

Sep 15, 2019

Too many errors in the code and explanations. Makes it very difficult to understand which is the right procedure/conclusion.

By Adam J L J H

May 24, 2020

This course focuses a lot on the theory and explanation. However, there isn't much hands-on practice for the coding itself.

By Osama W

Aug 25, 2020

*No response to some questions/comments on the forum

*More details/thorough clarification required for some points covered

By Rishika A

Mar 26, 2020

There are many errors and this was even the toughest course I have taken yet since many things were not explained clearly

By Kuzi

May 6, 2020

Course is flawless but when i had a technical challenge the Coursera team were clueless on how to fix it.

Otherwise good.

By Akash T

Jul 11, 2020

Few of the video requires improvement in terms of its quality. Particularly the lectures corresponding to week 4 and 5

By Teofilo E d A e S

Apr 16, 2019

Too complex for easy understand. Should have some documentation explaining the process and comparing the new methods.

By Julia S

Feb 11, 2022

It is okay in the sense that you learn something but the questions should be harder and it should go more in depth.

By Vrinda M K

Nov 25, 2019

Topics covered are important but videos end abruptly as if narrator was saying something more and video just ended

By Marc T

Feb 3, 2020

why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

By Abhishek K

Aug 26, 2019

Model creation and analysis part are too short, should have more details to understand the concepts better.

By Sarah S

Jan 2, 2019

This course seems to have an exponential increase in a learning curve. It seemed to be all over the place.

By Sara J H

Jan 6, 2023

Will be easy if you have prior experience with Python/statistics. I don't and I didn't learn much at all.

By Ramakrishna B

Jun 19, 2019

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections