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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
17,670 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.

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1926 - 1950 of 2,711 Reviews for Data Analysis with Python

By Tejpraneeth

Mar 25, 2019

good

By PALEM A

Mar 10, 2019

good

By Mahesh H

Mar 9, 2019

GOOD

By VISHNULAL M

Mar 9, 2019

nice

By Subrahmanyam

Mar 5, 2019

good

By Girish J

Feb 3, 2019

good

By Jimut B P

Sep 22, 2018

nice

By Sai S P

Apr 11, 2022

hhj

By Usman R M

Apr 27, 2019

top

By YANAMADALA P

Apr 3, 2019

gud

By Rex S A

Nov 29, 2022

..

By Yacin A M

Nov 16, 2022

hi

By SHREYANSH J

Feb 3, 2022

gg

By Talha A

Sep 16, 2019

<3

By Nikita C

Mar 4, 2024

k

By LALITHA K M

Nov 1, 2022

.

By Mohamed B

Sep 26, 2022

a

By Chandra S

Aug 7, 2021

By Ali C B

Dec 20, 2020

.

By Juan P

Apr 7, 2019

g

By Gaurav D

Apr 3, 2019

E

By Nat N

Sep 10, 2023

The Data Analysis with Python course is a decent intro into data handling, cleaning and some basic model building. I would say however that without prior Python or data analysis experience, it is probably quite a steep learning curve. I am from a science background with a bit of advanced maths knowledge, and the Model evaluation part got a little bit crazy even for me, I'll probably have to revisit it a few times. But you also can't expect to do a course like this and have a complete grasp of everything guaranteed, still have to be willing to do your own further reading/research outside of it, just like you would for uni. Some of the notebooks contained errors or the answers were spelled out which was a bit disappointing. My last project was graded immediately which was great, and I made sure to grade a couple extra to help other learners. Over all a great intro into some trickier topics, I enjoyed it.

By Armagaan

Feb 23, 2019

I had to remove 1 star just because of the fact that a project is not included in this one. Yes, you do have labs but there you are forced to write code in way so that you don't encounter problems later in the notebook.

In a project or an assignment work, you have to play with variables and confusions and errors out of wonderland show up which lead to greater clarification.

The course in itself is great and undoubtedly good in functioning as a prerequisite for Machine Learning and surely I'd recommend it to anyone who asks for an opinion. The explanations are good and much easier to understand along with the visual demonstrations.

I'd advise that after learning anything during this course, look for some database online and play with it yourself(I didn't but had to regret cuz I'd forget the code again and again).

OVERALL : GO AHEAD, it's worth it

By Sid G

Jun 11, 2019

The final assignment for this course is frustrating because it uses Watson Studio instead of the learning environment we've used up to that point in the course. There is registration, learning curve, additional complexity. One of the final questions doesn't accept a file upload. One of the questions asks you to calculate a regplot which takes about 15-20 minutes to complete. Nothing tells you to expect that until I finally found a student comment in the forum. I was so frustrated at one point I was ready to abandon the course because I didn't know what was wrong and couldn't find any help. The issues with the final assignment need to be addressed, but I'm glad I decided to stay with it. The course presented a lot of good material. I recommend the course, but I hope they will address the rough edges.

By Steven T

Oct 28, 2018

Overall a good introductory course. It features several interesting aspects of pandas, numpy and matplotlib. The focus lies on using statistical methods in Python, not on explaining statistics itself, bu a qualititative (short) explanation is given for all the items shown in the course.

A few things could definetly be improved:

Some parts of the videos or their accompanying notebooks have some errors and should be checked.

The course kinda suffers from only testing he students via quiz options. While the structure ad high frequency of the quizzes is to be commended and helps students stay on topic, there should be some final assignment hich consists of actual coding tasks. Not too difficult, but with some of the methods explained each week.