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

4.7
estrelas
12,475 classificações
1,808 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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51 — 75 de 1,788 Avaliações para o Análise de dados com Python

por Aldy P S

7 de Mai de 2020

helps me a lot! FYI I was new to data science and programming language but this course helps me to understand business analysis with Python!

por Ted H

6 de Jun de 2019

Covers a lot of ground but the Python Labs are great at bringing everything together.

por Paulo B M d S

4 de Jun de 2019

A very complete course of Data Analysis.

por Mahmood H

16 de Mar de 2019

Tough but useful.

por Vincent Z

10 de Mar de 2019

The course content is definitely interesting, but the approach is superficial. You will get a broad overview of the keyword to search for, and what is available in popular Python packages. However, the quizzes are way, way too easy. The course needs a final "open" assignment, where you have to use the tools without being guided along the way. This is the only way to truly learn.

por Mahvash N

4 de Mar de 2019

Course was great but it had number of errors and typos, that per my experience and other attendees caused some confusion.

I am sharing so it could be improved as it is a dream come true for myself to gain this valuable knowledge as conveniently as possible.

Thank you.

Mahvash Nejad

por Natalia Z

21 de Set de 2020

A very comfortably created course - no stress at all. However all that you can get is become familiar with the data analysis tools. May be that's the point.

por Ruchir

19 de Dez de 2018

I think few more practical exercises or at least references of the same would help better understand the overall fundamentals.

por Rebecca V

5 de Mar de 2019

Material covered is useful, but there are a lot of typos and mistakes in the lecture slides and labs.

por Rene P

24 de Mar de 2019

There could be links to functiones libraries in the lab for a fast check of a function if needed.

por Charles C

5 de Fev de 2019

Some mistakes/ typos in the exercises and slides, but great overall

por Yogish T G

30 de Mar de 2019

An assignment should have been included

por Niko J

29 de Abr de 2020

The course included a lot of very useful information. Thank you for that! Unfortunately it is also full of mistakes/misinformation. Every time I was about to report those errors, I found out that they have been already reported in the forum. And usually reporting had happened several months ago so that left me wondering how it can be that the mistakes are still there. So far I've been participating two other Python/AI courses by IBM and they were 5 starts. For this one, unfortunately 3 stars is best I can give with all the unfixed mistakes..

por Miguel E M

15 de Abr de 2020

There where some typos in the labs that could confuse most learners. I didn't feel like the course prepared people for real applications. The final project was quite hard because of this .

But it does give you a wide vision on hoy pandas work and some basic but apparently often used tools.

I see this course as a complement to a more detailed data analysis resource or perhaps as simply as an introductory view.

por Jaime V

22 de Fev de 2019

Hello,

in this course there were some errors on the slides, and some quite complicated topics (almost every time related to statistics) was given in a very over-viewed way. Also, some of the python codes were not explained very well, with some terms of them seem to be kind of arbitrary for those who are beginners in the language. My impression is that this course should be longer and more detailed.

por arda

20 de Nov de 2018

Overall I benefitted the course material as a beginner in python and data analysis. The questions were too trivial but maybe that helped me remain engaged with the course and complete it in a short time frame. There were some bugs, typos and minor quality issues that did not really effect my overall experience.

por Katarina P

27 de Jun de 2019

Many typos in videos, stats explained on a very rudimentary way (and often inaccurate), Watson environment is awful as it takes ages for some simple regression plots to be made, it freezes and the interface is not user-friendly, yet we have to use it.

por Sadanand B

7 de Fev de 2019

Seems like there are quite a few errors in the labs that confuse the heck out of a student. The labs need to be fixed else the material becomes useless.

por Ravindra D

11 de Mai de 2020

Course content does not give proper understanding of the different approaches. For the person who is not from mathematics background it is confusing.

por Bhuvaneswari V

9 de Mar de 2019

The statistics background needed for the course need to be better explained. or at least reference to related learning materials to be given

por Russell K

26 de Abr de 2020

Too many errors in the lab examples can be rather confusing.

Also, the Seaborn code was not working in IBM Watson Studio

por Mariam H

2 de Mai de 2020

Great course but some of the concepts are not explained very well. I got lost towards the end but overall i like it.

por Andre L

10 de Mar de 2019

Lot of information, but offered in a very choppy manner. Was hard to follow, will need to review many many times

por Abdulaziz A

11 de Abr de 2020

the course content is excellent but some Technical issues occurred in doing the lab exercises

por stijn d b

29 de Dez de 2018

i was following nicely until week 4 but halfway there it got really difficult. To a point in week 5 when all i could do was copying code and adjusting it. I have no idea what i was doing, i totally lost the bigger picture. I'm sure i could never replicate any of it outside the course or explain what i learned.