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Comentários e feedback de alunos de Análise de dados com Python da instituição IBM Skills Network

4.7
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15,309 classificações

Sobre o curso

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....

Melhores avaliações

RP

19 de abr de 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.

SC

5 de mai de 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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1576 — 1600 de 2,315 Avaliações para o Análise de dados com Python

por saiganesh g

11 de mai de 2020

Happy

por Mauro M M R

23 de mar de 2020

great

por kuncoro a n

18 de jan de 2020

goood

por Diego B

18 de dez de 2019

great

por Arnab C

15 de ago de 2019

best!

por Kathleen P

31 de dez de 2018

Great

por Hanafi R J

27 de jul de 2022

Nice

por Kevin L

3 de mai de 2022

Good

por 121910304029 D A

28 de abr de 2022

GOOD

por Santosh S H

26 de abr de 2022

Good

por 121910309055 K S D

25 de abr de 2022

good

por Dibyendu s

28 de fev de 2022

nice

por Omar C V L

14 de fev de 2022

Good

por Mohamed E

27 de out de 2021

good

por Satish w

27 de set de 2021

good

por Pradeep K

13 de set de 2021

Good

por Md. S I S

11 de set de 2021

nice

por Isabella A T

6 de set de 2021

Good

por Kofi D

17 de ago de 2021

good

por Yuqi X

3 de ago de 2021

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por Sarath M

2 de ago de 2021

good

por harsh h

30 de jun de 2021

good

por Swati P

9 de jun de 2021

nice

por Nikhil B

5 de jul de 2020

done

por Zixuan D

29 de jun de 2020

good