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

4.7
estrelas
12,454 classificações
1,806 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

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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1626 — 1650 de 1,788 Avaliações para o Análise de dados com Python

por A P

14 de Jun de 2019

Lots of spelling and grammatical errors that made it difficult to understand some of the material. It is otherwise an interesting course.

por 靳文彬

11 de Mar de 2020

There is no slides to download or review after class which makes it hard to go over the knowledge again without watching the video again

por Siwei L

23 de Jan de 2020

The video is too short and many concepts remain unclear or poorly explained. More contents need to be added to the questions and tests.

por Carlos R

26 de Mar de 2020

It's an excellent course; the best part is the labs. It's a pity that we (the students) have a lot of problems loading the labs.

por Pedro F

22 de Ago de 2019

Little bit confusing, unstructured and not easy to follow. Material inside is good though, but the course needs to be improved.

por sangeet a

8 de Abr de 2020

Things are too fast in this course and many things remain unexplained which makes it difficult for one to understand properly

por Dominic M L C L

15 de Set de 2019

Too many errors in the code and explanations. Makes it very difficult to understand which is the right procedure/conclusion.

por Adam J L J H

24 de Mai de 2020

This course focuses a lot on the theory and explanation. However, there isn't much hands-on practice for the coding itself.

por Osama W

25 de Ago de 2020

*No response to some questions/comments on the forum

*More details/thorough clarification required for some points covered

por Rishika A

26 de Mar de 2020

There are many errors and this was even the toughest course I have taken yet since many things were not explained clearly

por Kuzi

6 de Mai de 2020

Course is flawless but when i had a technical challenge the Coursera team were clueless on how to fix it.

Otherwise good.

por Akash T

11 de Jul de 2020

Few of the video requires improvement in terms of its quality. Particularly the lectures corresponding to week 4 and 5

por Teofilo E d A e S

16 de Abr de 2019

Too complex for easy understand. Should have some documentation explaining the process and comparing the new methods.

por Vrinda M K

25 de Nov de 2019

Topics covered are important but videos end abruptly as if narrator was saying something more and video just ended

por Marc T

3 de Fev de 2020

why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

por Abhishek K

26 de Ago de 2019

Model creation and analysis part are too short, should have more details to understand the concepts better.

por S A

2 de Jan de 2019

This course seems to have an exponential increase in a learning curve. It seemed to be all over the place.

por Ramakrishna B

19 de Jun de 2019

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections

por Camilo P T

15 de Jun de 2020

Creo que le hace falta unas guías, toda la información se da por videos. Recomendado para principiantes.

por Kenneth S

12 de Jan de 2020

As always, the final project always ruins good courses. LAZY design of the projects is unacceptable.

por Bjoern K

14 de Jun de 2019

Week 4 is somewhat hard to follow - Here, an overview over the different concepts would really help

por Nadeesha J S

11 de Abr de 2019

I would like to see a final project in this course. It will encourage the learners to do more work.

por Edward S

2 de Ago de 2020

The week 4 lab had issues with pipelines and did not function well and the final exam locked up.

por Miguel V

12 de Nov de 2020

Needs more information on statistical tests. Specifically, when to use one model over another.

por Poorna M

24 de Jun de 2020

Videos in this section could be little more descriptive. It was not in the pace of a beginner.