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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,466 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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926 - 950 of 2,886 Reviews for Data Analysis with Python

By Edwin K

Apr 9, 2020

I enjoyed the course because the labs were helpful for me to learn

By Bakari D

Jul 22, 2019

Great basis for developing regression models and model evaluation.

By Osinowo P

Jul 15, 2019

Not a bad course but you need to still do your homework thoroughly

By Gaurav K

Nov 4, 2018

This course covered the basics of data analysis. Could be improved

By Aniekan O

Apr 3, 2024

I enjoyed every bit of it. Great courses for beginners especially

By Pratyush G

Oct 3, 2023

Amazing course with lot of in-depth info, i thoroughly enjoyed it

By Elsa H

Jun 11, 2021

For me, a Python user beginner, this course was quite challenged.

By Heriberto F J

May 28, 2020

Excellent course to learn the basics of data analysis with python

By Andre F L

May 26, 2020

I think you should stress the pipeline subject a little bit more.

By Dominic F

May 14, 2020

Very well structured and organized. I really enjoyed this course.

By Nữ H

Apr 23, 2020

The course has clear instruction which is essential for beginners

By Jinjin X

Jan 27, 2020

It is a good course to learn Python techniques for data analysis.

By Praveen V

Oct 17, 2019

Thanks for the wonderful and concise course. It really helped me.

By Nipol C

Jul 26, 2019

This course provides you with good introduction to data analysis.

By Rabia M

Mar 15, 2024

Thank you so much to all the instructors for an awesome course!

By ramya c

Jan 13, 2024

Very Good course. Training was good. I learned a lot. Thank You.

By SUDESHNA K

May 24, 2023

It's very elaborate and good for all regression related problem.

By syed m u h

Jun 16, 2021

This course helped me to understand how to conduct data analysis

By Björn J

Apr 2, 2021

Great online class to start with python in a statistical context

By Nicholas S

Mar 15, 2021

Great course, easy to follow along and introduce basic ML skills

By prasannagp_cse M

Jan 18, 2020

Excellent assignments to take challenged work at the end of week

By Joshy J

Oct 31, 2019

One of the best course in IBM Professional certification program

By Ioseb M

Dec 21, 2018

Great Course. It took some time to be finished but it 100% worth

By 于小涵

Aug 8, 2024

It's very useful and teachers taught us in a rather clearly way

By Sebastian F

Aug 8, 2022

Lots of good stuff here ! thank you for such elaborated course!