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

4.7
estrelas
15,077 classificações
2,271 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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1776 — 1800 de 2,276 Avaliações para o Análise de dados com Python

por Saurabh A

1 de ago de 2020

Good course for beginners. Can introduce little more concepts such as multi-collinearity, model accuracy etc to make it even more complete.

por Victor D S C

7 de jul de 2021

A great explanation of the concepts and methodology in data analysis , i wish we couldve gotten more peer reviews like the last excercise

por Shreyas S

31 de jan de 2020

It was a good course overall. Would prefer explanations at a slower pace and more examples for each of the techniques explained.

Thank you!

por TooMuchSauce

14 de nov de 2019

Content : 5/5

Labs : 5/5

Final Assignment : 3/5 (It was quite easy to complete as there we instructions and code already written for you).

por Prasad T

29 de jan de 2021

need better practise questions preferably to write program instead of multiple choice answers plus needed more theory of the topics given

por Jonathan B

25 de jun de 2020

Great material. Very comprehensive. The only knock is sometimes the slides, notebooks, and quizes have typos or are not super-organized.

por Aurelio L G

17 de jan de 2020

Una visión muy amplia con acercamiento a una amplia variedad de herramientas. Faltan más ejemplos de uso, ejercicios y casos prácticos.

por Subhasish D

13 de jul de 2020

The learning are too basic, trust me in real world things are much critical. Probably coursera can help us with that kind of knowledge

por William O

27 de mar de 2020

One the greatest course of Data Analysis. The info given about statistics is very important and accurate.

Thank you to the instructors.

por Matthew A

12 de mai de 2019

The more advanced portions of the course felt a bit rushed without enough examples and hands-on work to really reinforce the concepts.

por Jan M v d B

24 de jul de 2021

Learned a lot about statistical analyses in this course, but the easiness of the assignment and grading quizzes make it unfulfilling.

por In W C

3 de out de 2019

Other than some minor errors and bugs, I think this course gave good introductory material that can be supplemented with other books.

por Cindy N P P

10 de mai de 2020

There should be another grading method for the final task, that a system is in charge of assigning the grades, not other classmates

por Oscar J C

21 de jan de 2020

The course is well designed, however, in some videos exist misspelling functions that may confuse when you try to test on your own.

por Sujith K S

20 de out de 2020

Seemed a bit rushed towards the end. Advanced topics such as pipelines, polynomial transformation, etc were not explained clearly.

por Maddipudi p

24 de dez de 2020

content is great.playback speed can go bit slow for students like me from India language is bit hard to understand at that speed.

por Tianyue Q

26 de abr de 2022

Give a general overview of how to do data analysis with a brief intro of how to apply machine learning in a real life scenario.

por Tsungai J M

12 de out de 2019

Some areas were a bit complex and required additional reading outside of the content provided but overall I enjoyed the course.

por Marc S

30 de jun de 2019

Great course explaining some data analysis techniques. Some minor errors in voice track and material, but overall good content.

por ASIF I T 1

13 de mai de 2022

The course was really good. But I would've liked to face more problem statements to practice what I was taught in this course.

por Ajith B

14 de jul de 2021

Good Course. But many content's have been packed in this small one , I guess additional reading content could have been given.

por Jorge I L C

19 de ago de 2020

muy bueno, este curso deberia ser el 2do o tercero en esta seccion, se ve bastante de lo que usa un data science normalmente!

por RANGA D

28 de abr de 2020

Good for an individual who is passionate about data science

Thanks course era for providing the course

#datascience enthusiast

por RICHARD D

11 de out de 2019

This course give a brief Understanding Of Data Analysis with python. Thanks to the IBM for making us part of The IBM family.

por G D

24 de ago de 2019

This is the good course for beginners. Great Explanations for pandas, EDA and scikit learn model analysis. Good to try this!