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

12,738 classificações
1,850 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

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.

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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1501 — 1525 de 1,834 Avaliações para o Análise de dados com Python

por Moaz A S M

11 de Out de 2019

some topics have not been covered well like piplines , cross validation

por David O

26 de Jul de 2020

The materials are well-organized, but there are many typos throughout.

por Angeliki M

2 de Dez de 2019

A really good course. Probably the best so far in the IBM Certificate.

por Nanjun L

9 de Jan de 2019

Would be better if more programming-oriented assignments are provided.

por Rahul P

12 de Mai de 2020

Excellent course with detailed hands-on experience via lab exercises.

por Manas C

31 de Mar de 2020

The course covers all the fundamental concepts needed for a beginner.

por Obong G

19 de Fev de 2019

Though found the ending modules a bit challenging, its a great course

por Padraig M D

7 de Jun de 2020

Quite a challenging course, but very rewarding. I really enjoyed it.

por mohsin a

17 de Out de 2020

Hands on Labs are awesome .They helped to consolidate my concepts .

por Rohit S P

25 de Abr de 2019

Needed a more brief explanation on ridge regression and grid search

por Ninad M K

14 de Jul de 2020

It is a great course and it teaches me data analysis with python.

por Ginger M

18 de Mar de 2020

I think that for weeks 4 and 5 the course needs more explanation

por Wen P

24 de Dez de 2019

Easy understanding

Good sample and comprehensive

Good for beginner

por Jeff J

27 de Ago de 2019

Nicely explained. But many minor mistakes here and there though

por Bashar M

5 de Fev de 2019

thank you very much ,this course was very useful and interesting

por Cherif H W A

14 de Dez de 2019

as usual the labs are great but the videos could be much better

por Nicholas J F

3 de Mai de 2019

Good content. Still spelling errors and mistakes in some place.

por Mudita N

20 de Fev de 2019

Last few weeks were a bit confusing but overall a good course .

por Ismayil J

5 de Nov de 2018

Good overview of classic Statistic methods performed in Python.

por Shine

18 de Jun de 2019

There are something wrong in the final assignment submit page.

por Tatiana K

25 de Jan de 2019

Great course, but the number of errors in videos is tremendous

por Yongda F

16 de Jun de 2020

This is a good course for beginners, but not enough in-depth.

por Eliezer A

30 de Jul de 2019

there are some errors in the code lines through the lecutres.

por WANG T

24 de Jan de 2019

Typos in the videos and notebooks should have been corrected.

por Alvaro H A C

30 de Set de 2020

Buen curso, los talleres permiten la aplicación de conceptos