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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
7,394 ratings
911 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

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.

OA

Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

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626 - 650 of 908 Reviews for Data Analysis with Python

By Logan W

Nov 08, 2019

This was a very comprehensive course, but it could definitely use some revising on the labs that caused output issues. Additionally, some of the peer-graded material couldn't be uploaded due to syntax. Other than that, very helpful!

By asher b

Nov 12, 2018

this course finally gets to some key Python functions for data analysis. Some of this may be difficult without a basic stats background. Only knock is there are MULTIPLE typos in the slides and labs. Needs to get fixed.

By Ankit S C

Jan 15, 2020

The Model Training and Evaluation weeks could have been more elaborate. Instead of just telling to do something, it would've been better to explain why we are doing it and how is it working internally, at a high level.

By Junior N

Aug 18, 2019

This course is pretty good and give a good introduction to data analysis with python. However, there is a problem in the course's methodology : functions are given without any introduction...just implementations.

By Keerthi S

Nov 03, 2019

The final assignment had some errors in submission with some questions not allowing for upload of the answers (Question 3, i.e.). Did not feel great about this error. Otherwise, great course - very useful.

By Mantra B

Nov 03, 2019

Overall a great course. All essential Data Analysis processes are covered in this course. A small nitpick is that Week 5 material was a little less in depth. Moore examples in videos will be a great help!

By Saptashwa B

Jan 18, 2019

Great course for introductory data analysis with Python. Very good for fundamental understanding of overfitting, underfitting, precision, accuracy and using grid search method to optimize fit parameters.

By Brijesh D

Nov 23, 2019

Really interesting course, if one wants learn programming language. Well designed and structured. Only suggestion is, if the small videos contains example that be really great to understand it well

By Rahi J

Oct 17, 2018

It will be helpful if a video is added on:

1) how to store multiple results from different models in single dataframe

2) how to automate the process. More example needed on Grid and Pipeline.

By Rodrigo D

Feb 24, 2019

Great course, you can understand in a general way the use os Python to analyse raw data and organice it to create a better model. However I couldn't use in a proper way the external tool.

By NAPA S M

May 08, 2019

Questions while listening to lessons in some of the lectures are coming before theory explained by the teacher .Better if question is at least 10 seconds after related theory explained.

By Daniel A

May 31, 2019

This was pretty good, I think maybe the best in the IBM machine learning certificate. I took Andrew Ng's course prior to this, so to watch python sklearn in action was a real treat.

By SHALINI G

Oct 01, 2018

It is a good course for beginners but I feel that the quizzes could have been a bit more challenging. And if the codes were executed in the Python domain , it would have been nice.

By mitul p

Nov 09, 2019

Very interactive and informative content.Covered all the data analysis related concept. I would suggest that spare some more time on Regression techniques to details information.

By RAVIKUMAR M

Dec 08, 2018

Good content through out the learning, the lab notebooks are great resource to do the Hands on by ourselves. Includes each corner of the analysis methods. Good foundation course

By Sam T

Jun 10, 2019

Course provides a good intro and the visuals are great. It doesn't however go deep into each topic and doesn't provide enough examples to explain concepts for different cases.

By Mark H

Feb 10, 2019

Pretty dry material. Hard topic to teach since the process really comes from experience. Could stand to focus a bit more on ways to explore and clean data. Not bad though.

By Andrew B

Jan 26, 2019

Good for a first course in data analysis however this course covers the subject on a very superficial level. There are a few errors in the assignment's solution guide.

By Rahul S

Apr 10, 2019

Good but in the end of the course specially week 4 and week 5, speed of information providing in videos get to very high speed comparative to other weeks information.

By Krithin K V

Dec 02, 2019

Some of the topics at the end of the video have been rushed to end. I would rather liked to see an elaborate examples for those topics to atleast have an idea of it.

By Harshit T

Sep 22, 2018

Fun course! Lots of interesting content. It could've been more interesting and challenging with addition of a couple of marked assignments or a capstone project!

By Kedharnath A

Apr 15, 2019

I found this module very difficult to understand as it was loaded with high end concepts and coding. Might have to redo this course to understand even better.

By Manoj S

Mar 10, 2019

Course content is very good but I feel it can be more improved if the training is provided at slower pace. Also the examples should be in detail. Overall good

By Faizan A S

Dec 01, 2019

The course content is really great and method of teaching is very specific .Much details very covered during the course and really i gained a lot from this.

By SOUVIK B

Aug 31, 2018

Good course if you are beginning data science. You don't need much of python experience but will be better to have if you want to quickly finish the course.