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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,528 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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2826 - 2850 of 2,898 Reviews for Data Analysis with Python

By ubaid m w

Oct 22, 2018

In lab there are many funtion , libiraries Which have been used first time with out any description , then I have to search for each and every funtion or lib which is way time consuming which make this course worst courses in my list.

By jitao f

May 2, 2019

The content of this course is too basic. Though it provides enough knowledge to start a practice. No 0 to 1 but more like 0 to 0.1. And Forum support is terrible. Can't really answer my question( don't even think they have read it ).

By Zac M

Oct 29, 2019

The topics are great, but the content is pretty terrible. The questions are incorrectly formatted and hard to understand. It would be nice if someone reviewed these before they make them live and you have to pay for them.

By Brahmrysti A B

Jun 2, 2020

A lot of mistakes here. Clearly rushed and not given the care and attention it needed. Some assignments REQUIRE you to go to the discussion board to figure out what the author intended and why your code isnt working.

By Ashish D

Dec 22, 2019

Does the job of a good introduction.

Very limited and restrictive practice and assinments.

For a true learning experience one needs to do a lot of external research and work to show a measureable benifit.

By Steve H

May 19, 2020

The content is good but there are a lot of mistakes and typos in the material. The peer review is extremely vulnerable to errors - only one person reviewed my assignment and gave me the wrong mark.

By D W

Aug 17, 2019

Useful course but riddled with typos & inconsistent questions and answers. Needs a proper review by someone (probably not the people answering on the forums, who didn't seem especially clued up).

By Aaron C

Jul 15, 2020

The videos really are not very engaging (relative to any other course that I have completed here on Coursera). The concepts are not explained very thoroughly. Thanks anyway guys.

By Berkay T

Sep 27, 2019

Too much content, so less practice. This course doesn't teach anything that you can make use of in the long term. It only gives an idea on what you have to work on in the future.

By Sheen D

Aug 11, 2019

This is by far the worst course in the specialization. So many mistakes in the lab session, including unclear instruction, or syntax is not uniform across each module, and etc.

By Cláudia S B

Jul 16, 2021

The artificial voice used over the video is truly awful for learning. I enjoyed the jupyter notebooks where I actually could learn what was bla-bla-blaed in the videos

By Michael M

Dec 20, 2019

The IBM Developer Skills Network (at labs.cognitiveclass.ai) is very slow and doesn't work most of the time.

It doesn't allow to finish the course properly.

By Ismael S

Jun 2, 2019

Content is thrown to the student with too much information and videos of only 3-4 minutes. Too much to absorb and too little to practice properly

By David K

Apr 28, 2020

Too many errors. Please renew the course asap for the future learners. These errers are distracting and make the learning experience less fun.

By Archana B

Apr 28, 2021

Model Development and Model Evaluation & Refinement Concepts are not explained properly neither in Videos nor in Lab!!Really disappointing :(

By Tarun S

Mar 10, 2021

Concepts of the algorithms are unclear. In the notebooks as well, it is not in a flow. Very confusingg for a beginner to learn from this.

By Malcom L

Jan 11, 2019

more hands on, project based/game based learning. Mindlessly watching videos and regurgitating code in the labs can not be the only way.

By Santanu B

Apr 16, 2019

Not a great course. Sometimes it is too fast and the explanations are very short. More hands on exercises would have been more helpful.

By Rajesh W

Oct 17, 2018

There are plenty of mistakes in the videos and in the lab session as well. Hope you guys can clear out those.

By Wayne W M

Oct 2, 2019

This was a very challenging course. Some concepts were difficult to grasp and required additional research

By Mark F

Apr 8, 2020

Frustrating when the peer reviewer doesn't actually understand Python and deducts marks for correct code.

By Hunter I

Apr 17, 2020

Leaned some, but not a whole lot of real-world application, I recommend people take Python courses more

By Ashwin D

Apr 29, 2020

Not enough hands on problems, including variety and volume. Expected more from an IBM program.

By Nathaniel S

Mar 29, 2020

Don't spend your money on IBM Data Science Cert. Course labs are full of bugs and not working.

By Katherine L

Jun 5, 2022

coursework was easy but that damn final assignment was absolute hell for no reason whatsoever