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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 Skills Network

4.7
estrelas
16,195 classificações

Sobre o curso

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

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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2276 — 2300 de 2,447 Avaliações para o Análise de dados com Python

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.

por Nathan P

1 de jan de 2020

It was cool to see the stuff at work but I need more hands on practice to really learn stuff.

por Varun V

18 de dez de 2018

This looks good for experienced but not the best of course for beginners/intermediate level.

por Connor F

27 de mar de 2020

when it got to model development it got too complicated too fast. The first half was great.

por Badri T

28 de mai de 2019

Lots of good concepts. However, too complicated and could have been explained a bit more.

por Jesse Z

5 de jun de 2019

For such a important topic, it seems like the videos sped through some essential topics.

por Debra C

24 de mar de 2019

Course was worthwhile for general understanding of what can be accomplished with Python.

por Miguel A I B

13 de mai de 2020

Exelent training to get familiar and intruducing to Python capabilities and programing

por Xinyi W

26 de jan de 2020

Superfacial level of Python while being not very through on the data analysis methods.

por Ana C

11 de jun de 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course

por Sathiya P

27 de ago de 2019

Nicely thought, but I felt concepts like Decision trees, Random forest were missing

por Ros R

12 de ago de 2019

The course is too long. The material should be divided and explained more detailed.

por Amanda A

16 de abr de 2020

There were many typos in the labs which made it difficult to understand at points.

por Juan S A G

20 de ago de 2020

very simple exercises which does not help to learn altough videos were exeptional

por Nafsika G

1 de nov de 2022

It was a good course but maybe a little too easy with all the prompts provided.

por Mohsen R

16 de jun de 2020

The course does not explain the processes enough, there should be more examples.

por Maciej L

16 de mai de 2019

Too many complicated things happening at once. It is hard to digest and follow.

por Tomasz S

19 de nov de 2018

Few small hiccups with the training videos and quite a few in the lab-excercise