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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
11,641 ratings
1,676 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 06, 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 20, 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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1576 - 1600 of 1,660 Reviews for Data Analysis with Python

By Ashwin G

Apr 26, 2019

Too fast and could have included more examples.

By Gerhard E

Feb 12, 2019

Copy of videos, not a fan of tools used in labs

By ABOUDA Y

Feb 03, 2020

Un cours riche et adéquat pour les débutants

By Ambe E

Nov 27, 2019

Very nice course. It gives you what you need

By Brian S

Mar 29, 2020

Notebooks are sloppy, with typos and errors

By Sachin L

Sep 26, 2019

More examples and detailed explanation

By Nilanjana

Jul 12, 2019

More examples and code examples needed

By Hamed A

Apr 09, 2019

The course needs a final assignment!

By piyush d

Dec 06, 2019

exercises could have been better.

By Jyoti M

Mar 26, 2020

I felt it was too fast to grasp.

By Baptiste M

Nov 02, 2019

Final assignment is quite messy

By Yuanyuan J

Jan 18, 2019

Not clear on the last part

By Ahmad H

Jun 08, 2019

This course is very tough

By conan s

Dec 20, 2019

Lots of technical issues

By David V R

Jun 17, 2019

Exams should be harder

By Riddhima S

Jul 08, 2019

la lala la la laa aaa

By Daniel S

Feb 09, 2019

Not easy to follow.

By Vidya R

Apr 16, 2019

Very Math!

By Alex H

Oct 05, 2019

Begins relatively clear. The practice labs were coherent and straightforward.

Around Week 4, things started to get convoluted. Small things, things that you don't notice at first.

Week 5 was where it really started to fall apart. You could tell whoever made this course lost interest or just did not have the capacity to teach the information effectively.

A great example of the lack of understanding or knowledge of how Coursera works is something you can view yourself.

Week 6 is the Final Project

Week 7 is one statement about your certificate.

Usually in most courses, the final project will be in end of the final week. That week having multiple modules that you have to complete leading up to the final. It was worrying for me as I thought the approach to this was on accident, but it seems likely that it was just due to ignorance.

Just as well, the Final Project was botched, the software and questions were depreciated and even written wrong by the creator. And when you would upload your pictures in the end to show you had worked out the problem, one of the upload buttons was missing in lieu of the letter "Y"....

Y indeed. Y was the ending of this course so terrible? A little more investment in the people you are teaching would go a long way. Very disappointed.

By James H

Apr 29, 2020

Definitely not one of my favorite courses in the Data Science Certificate series. There were times I was ready to give up the pursuit of the certificate altogether during this class... There should have been a prerequisite for this course of the statistical tools and methods that would be covered in here... Sure I could program these things after this class, but i still dont understand why I would choose to use one over another? This is one of those classes where you walk away feeling more confused than when you went in... Also there were a lot of mistakes, typos, and obsolete things in the labwork - some reported and acknowledged months ago, but still not fixed in the lab (video I can understand, but not the labs)

By Ruben W

Oct 06, 2018

The content is good, but if you are not familiar with Python, I wouldn´t recommend this course. There are a lot of typos in the video. The code contains a lot of errors where you have to find a solution. So, you are forced to debug their code often.

But if you are only interested in the course certificate, you could quickly go through the videos and quizzes, without any problems. It's easy to pass because the questions are like: What is the result of print("Hello world"). So no real challenges at all.

Please, try to fix the typos. Sometimes it was very embarrassing. Example (Week 3) instead of

"from sklearn.metrics ..." the video comes up with "from sklearn.metrixs ..."

By Micheal D L

Jul 29, 2019

many typos, errors, mislabeled... just felt like a sloppy product were paying for. I was very frustrated as well by certain features not functioning... for example, after following specif instructions to share a notebook, just as I have done many times while working on this certification... testing the link comes back as unshared no matter what I do. This and the SQL course have been the worst so far in this Data Science cert but at least this course ended up marked as completed. If I wasn't already this far invested in the cert I would definitely quit and use free resources while I built my portfolio.

By Tom S

Mar 17, 2020

-1- The training and quizzes are full of errors. You need someone to actually review the content before publishing.

-2- The education focused more on the mechanics of how to run certain commands to obtain results rather than explaining why a data scientist would want to run these certain commands and how to best interpret them.

-3- I would embed more but perhaps smaller lab assignments rather than going over many concepts and making the person go through the steps (with minimal explanation) at the end of the module. This is particularly applicable for weeks 4 & 5.

By Joseph G

Jan 06, 2020

There were so many typos and errors about the very topics they were teaching. It is as if they don't actually care that people are trying to learn this and just view this course as a way to promote their Watson Studio. Normally I would forgive these errors, but there are programmers so paying attention to detail is paramount. Also, misspelling method names while you are teaching those very methods and then never showing how to spell them again makes for some serious confusion.

By Shaleen S

Oct 09, 2019

The final peer graded assignment has considerable coding issues. Regplot does not execute in the Watson Studio despite proper coding. During submission one question does not have the arrangement to upload JPEG file for submission so all you can do is post the code. The Q8 is dropped out of the blue with no reference availabe in any of the courses.

The course itself is very informative but it is very evident that no one is reviewing whether everything is working properly.