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

4.7
estrelas
12,956 classificações
1,892 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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1426 — 1450 de 1,872 Avaliações para o Análise de dados com Python

por Kedharnath A

15 de Abr de 2019

I found this module very difficult to understand as it was loaded with high end concepts and coding. Might have to redo this course to understand even better.

por Manoj S

9 de Mar de 2019

Course content is very good but I feel it can be more improved if the training is provided at slower pace. Also the examples should be in detail. Overall good

por Andrés C P A

30 de Jan de 2020

I think it would be good if the units had activities to deliver mandatory since that would allow to strengthen the knowledge acquired. Thanks for the course.

por Faizan A S

1 de Dez de 2019

The course content is really great and method of teaching is very specific .Much details very covered during the course and really i gained a lot from this.

por SOUVIK B

31 de Ago de 2018

Good course if you are beginning data science. You don't need much of python experience but will be better to have if you want to quickly finish the course.

por Sreelatha V

5 de Jan de 2020

Very detailed and guided course that provides an overview of data analysis in Python with short assignments after each video and interesting lab courses.

por Guilherme V

3 de Jul de 2020

insufficient statistic, as the name of the course is Data Analysis, i would expect more classes about the different distributions of data, pdf and pmf..

por Katarina S

22 de Mar de 2020

One of the best courses in the IBM Data Science Specialisation.

I would like to have more quiz questions and opportunities to practise what was covered.

por Frank

30 de Ago de 2019

I would have given it 5 stars but they barely went over polynomial regressions and pipelines and it was a major portion of the end of class assignment.

por Wenyu X

2 de Abr de 2019

pros: well organized, clearly explained each step, useful

cons: frequent errors in both videos and the lab, especially on the questions part in the lab

por Maksym S

3 de Set de 2019

Final exam was too complicated. I have 2 masters degree and for me it was clear, but for other it is too complicated.

P.S. it is my personal opinion

por BINAY K

6 de Jul de 2019

Course is good, but in this short course it is covering lot of thing thatswhy lot of topics are just touched intead of going little bit deep into it.

por Sergio F C C

20 de Jun de 2019

You learn a lot, good intro to data science with python. Labs have typos and can be confusing at times though, the only thing that could be improved.

por Aurangazeeb A K

13 de Out de 2019

A very interesting and easy course. Anyone can catch up with big concepts with little effort. Thank you Coursera and IBM for this wonderful course.

por Sucheta

2 de Set de 2019

Course is nicely designed and pare explained well.

I would have liked to see the steps along with the final answer to the peer assignment questions.

por zara c

31 de Out de 2020

Very good course. I wish there were more hands on exercises. We only had a chance to practice in one lab per module; otherwise, I learned a lot.

por Ponciano R

26 de Fev de 2019

Great course to start learning python applied to analysis, but after this, I prefer to use R. Less complicated and can obtain the same results.

por Sifat S

17 de Mai de 2019

I find this course useful. But some of the contents are little advanced all of a sudden and feels some important explanations are not covered.

por Venkatesh E

21 de Jul de 2019

Through out the course i have learned alot like data visualisation mainly.I think i have completed successfully basics for machine learning.

por Randall G

26 de Set de 2018

I feel like this section needs some more hands on labs. Great topic over view and application. Not to much in the way of math unfortunately.

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 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.