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

4.7
estrelas
14,945 classificações
2,247 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

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.

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.

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26 — 50 de 2,250 Avaliações para o Análise de dados com Python

por Peter A

16 de out de 2019

Too many mistakes in the lectures and the main lab. Confusing for new learners when the math is wrong or the python syntax is wrong. Anyone who rates this above 3 stars you are simply not paying attention to the myriad of mistakes.

por Ivo M

19 de dez de 2018

The course had plenty of errors in the videos, Labs and quizzes. The explanations were rushed at times and quite a bit was not easy to follow. The worst course so far!

por Javier M

28 de abr de 2021

The content is solid. However, the labs which are the best tools of this course because they allow you to actually do the exercises and go deeper in the concepts are not working. It has been like that for some weeks.

I contacted support and I saw in the course forum lots of people complaining about it but either Coursera or IBM don't seem to care. No answer from them for weeks. I had to dig into forums in the Internet to find alternative solutions to access the labs... which was a waste of time considering that I'm not auditing but paying for this course.

So terrible customer experience, that's why I put one star.

por Sobhan A

6 de mai de 2020

Low quality.

Do not recommend this course at all.

Boring teaching method.

Full of errors.

No IT support for problems.

por HIMANSHU S

30 de jul de 2020

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.

por Usman A

29 de jul de 2020

AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.

por Matthew A

13 de abr de 2021

During the 4th week of the course, lots of important information and explanations are over summarized and in some cases skipped over. Learning tools outside of what is provided in the course or a decent understanding statistics is required in order to be successful in this course.

por Vincent L

17 de set de 2018

Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.

Not professional at all.

por Thamarak

22 de ago de 2020

This course is too hard. This should be go on more slowly and explain more about meaning of each value described. The course is not for beginner and not for a person who doesn't have enough statistics background.

por Anastasiya B

22 de set de 2019

Low technical quality of the course with lots of typos, errors and comletely mess in final assignment.

Low quality of material, bad structure, and you can get your certificate just by clicking shift+ enter

por John K

7 de jul de 2019

Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.

por Titans P

17 de ago de 2020

worst ever

the greatest thing i have learned here is patience and searching online

por Uygar H

14 de mar de 2019

I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you

por Daniel T

9 de abr de 2019

This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s

por Shashank S C

6 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.

por Firat E

4 de jun de 2019

It is really a good course, simple to understand and very complete. Thank you !

por Ashirwad S

21 de mai de 2019

Recommended course to understand the how to do data analysis using python

por Jim C

20 de mai de 2019

Well organized, good explanations, and very good labs.

por Aditya M

21 de mai de 2019

Overall apt content for beginners and naive learners.

por Vineet M N D

20 de mai de 2019

Great experience

por Shernice J

30 de mar de 2019

Instead of having a lab after each topic, this course one lab per week encompassing all of the topics. Some might find that better than having smaller labs but to me the information was assimilated better when i did a lab right after the topic. That being said, you can open the lab first and follow along with/after each video. You just need to be mindful of what works best for you. Taking time to understand the code is a must and some more documentation would be helpful. I wasn't a beginner with Python and it took some time and work out what was happening at times.

por Akiru J C

12 de abr de 2022

I really enjoyed this course. Few things to suggest:

- Go over Statistics in more detail. Had I not studied Statistics in university, I may have found this topic confusing.

- Felt like I could have learned more if the labs were not filled-out halfway

- Too many multiple choice questions in the quiz and final. These should be more interactive with lines of code we would type insetad of clicking a bullet.

- The math covered in this course was very high level. I.e., Chi-square and linear regression require more hands-on practive in order to grasp.

por Itshak C

13 de abr de 2021

Loved the labs. Hated the Videos. The amount of information that is thrown at you in a 1 min video is very unsettling as it makes you think you haven't understood a word of what they say and then the labs immediately clear everything up and then you feel like the smartest person alive. It's an uphill battle at times but the end result is pretty helpful regardless of the reason you're perusing the course.

por Devansh N

5 de mai de 2020

Was a bit tough to keep up at the week 4 and week 5 but overall a very good course

por Nigel A R H

13 de mar de 2019

Quizzes are too easy. No evaluation of actual code.