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Voltar para Análise de dados com Python

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

14,451 classificações
2,144 avaliações

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

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.

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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2026 — 2050 de 2,140 Avaliações para o Análise de dados com Python

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 Jan 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 Out de 2019

The kernal is stuck for some questions and its annoying

por Qing L

26 de Jan de 2020

Kurs gut organisiert aber

die Fragen sehr oberflächlich

por Jakubina K

19 de Dez de 2018

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

por Ankit K S

29 de Jan 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 Jan 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 Fev de 2019

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

por Yasmin A

3 de Fev de 2020

Un cours riche et adéquat pour les débutants

por Hiro H

27 de Nov de 2019

Very nice course. It gives you what you need

por Brian S

29 de Mar de 2020

Notebooks are sloppy, with typos and errors

por Fariha M

28 de Set de 2020

The course didn't seem challenging to me.

por Sachin L

26 de Set de 2019

More examples and detailed explanation

por Nilanjana

12 de Jul de 2019

More examples and code examples needed

por Hamed A

8 de Abr de 2019

The course needs a final assignment!

por piyush d

6 de Dez de 2019

exercises could have been better.

por Jyoti M

26 de Mar de 2020

I felt it was too fast to grasp.