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Volver a Análisis de datos con Python

Opiniones y comentarios de aprendices correspondientes a Análisis de datos con Python por parte de Habilidades en redes de IBM

4.7
estrellas
15,259 calificaciones
2,301 reseña

Acerca del 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....

Principales reseñas

SC

5 de may. 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.

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.

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2176 - 2200 de 2,308 revisiones para Análisis de datos con Python

por Anvit S

13 de may. de 2020

Could have been more detailed....Important concepts just brushed thru

por Holly R

16 de abr. de 2020

Could use some better mathematical description of the techniques.

por Filippo M

27 de sep. de 2019

Useful course, but the IBM online platforms are not working well.

por Robert P

17 de may. de 2019

Some concepts were quite confusing and not that well explained.

por Atharva Y

23 de ene. de 2020

As compared to other courses this course seems to be too fast

por Nirav

26 de jun. de 2019

Lot's of errors in this course, please update and correct it.

por Anmol P

14 de oct. de 2019

Course could have been more elaborate in depth and scenarios

por Tichaona M

5 de ago. de 2020

This is a great course for building the base to use Python!

por 林tanya

27 de dic. de 2019

the lab is extremely useful, however, videos are too short

por Michael A D R

1 de nov. de 2019

Extremely interesting BUT it gets long and hard to follow.

por Nihal N

18 de abr. de 2019

not in depth.... needs more clarity on a variety of topics

por Alejandro A S

25 de jul. de 2019

Experimented a lot of problems to complete the assignment

por Troy S

14 de mar. de 2019

Quizzes are too easy. Don't even need to watch the videos

por Anurag P

18 de ene. de 2020

Mostly theoretical; very little to implement on our own.

por Pulkit D

29 de jun. de 2019

Please update and explain Rigid Regression a little more

por Appa R M

24 de oct. de 2019

The kernal is stuck for some questions and its annoying

por Qing L

26 de ene. de 2020

Kurs gut organisiert aber

die Fragen sehr oberflächlich

por Jakubina K

19 de dic. de 2018

It would be more useful if labs were be rated as well.

por Ankit K S

29 de ene. de 2020

It would be nice if the course had more assignments.

por Bhanu S

28 de abr. de 2019

It was difficult to retain the knowledge imparted.

por Alton M

8 de jun. de 2019

The course requires more interactive programming.

por Xiangyu L

19 de ene. de 2019

There are lots of mistakes throughout the courses

por Abdul M A

17 de abr. de 2019

Not very interactive with fewer help to learners

por Ashwin G

26 de abr. de 2019

Too fast and could have included more examples.

por Gerhard E

12 de feb. de 2019

Copy of videos, not a fan of tools used in labs