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Kursteilnehmer-Bewertung und -Feedback für Datenanalyse mit Python von IBM

12,083 Bewertungen
1,746 Bewertungen

Über den Kurs

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....



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.


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.

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601 - 625 von 1,728 Bewertungen für Datenanalyse mit Python

von hassan s

Aug 19, 2019

Thank god - Nice course and good perception of understanding.

von Amruta G

Jul 20, 2020

It is the best course for beginners to start with .Thank you

von Robin V

Mar 05, 2020

The course is well designed. Learned the concepts very well.

von Maaz A

Apr 14, 2019

One the very well defined and finest course I have ever seen

von Brian V

Mar 25, 2019

At least, I have learnt something new at a very basic level.

von Matheus L T A

Mar 15, 2019

Great! Filled with lots of concepts and practical exercises!

von Muhammad R

Mar 09, 2019

Good Course ,learn mant things about Data science in details

von David C

Dec 20, 2018

This one was a little more difficult than the previous ones.

von Gene M A

May 27, 2020

Well though-out format for teaching such a complex subject.

von Mpho L C

May 17, 2020

The course was awesome and delivered in an efficient manner

von Varun S

May 08, 2020

Extremely good course to begin your Data Science Journey !!

von Ninan A

Apr 01, 2020

Good course to quickly learn basics and start experimenting

von Mahomet N

Feb 24, 2020

The best course I've ever had on Coursera, very insightful!

von Ivan R A V

Feb 24, 2020

Excelente, muy agradecido por los conocimientos adquiridos.

von Zayed R

Sep 02, 2019

This course is providing valuable insight in Data analysis.

von Thanh C D

Jun 14, 2019

Great Course! A lot of advanced knowledge. Very valuable <3

von Yves B

Mar 03, 2019

Very thorough teaching of statistical analysis using python

von Amanzhol K

Jan 21, 2019

The most useful course on studying statistics in short time

von Valerii P

Nov 25, 2018

That was a great start for Data Analysis field's discovery!

von Rutav M

Oct 22, 2018

Good explanation for each topic and nicely designed course.

von charles l

Aug 19, 2020

Great course - really great notes, exercises and projects!

von Ashish S

Jul 11, 2020

Very good course learnt a lot and cleared a lot of doubts.

von Stan M

Jun 11, 2020

Great content. Ton of stuff to learn if you are motivated.

von Yiming Z

Mar 14, 2020

great experience with IBM data analysis with Python


von Hasan F

Feb 08, 2020

Concise but effective lectures, great learning experience.