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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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1701 — 1725 de 2,277 Avaliações para o Análise de dados com Python

por Orsolya N

26 de jun de 2020

Certain parts were too fast, and there were some technical issues with the labs at times, but there's always the possibility to look up the blurry parts online. Overall it was interesting and well put together.

por Kyle H

25 de fev de 2020

This definitely could be more project based than it was, and focus more on applying coding skills than just reading them and watching videos about them, but it's a great overview of some useful techniques.

por Keerthi S

3 de nov de 2019

The final assignment had some errors in submission with some questions not allowing for upload of the answers (Question 3, i.e.). Did not feel great about this error. Otherwise, great course - very useful.

por Mantra B

3 de nov de 2019

Overall a great course. All essential Data Analysis processes are covered in this course. A small nitpick is that Week 5 material was a little less in depth. Moore examples in videos will be a great help!

por Christian A S

2 de jun de 2021

Los procesos de practica asumen que el manejo estadístico, es solo dar el resultado, pero creo que el contenido es bastante profundo y la practica debe ser mas concentrada en evaluar diversos escenarios.

por Saptashwa B

18 de jan de 2019

Great course for introductory data analysis with Python. Very good for fundamental understanding of overfitting, underfitting, precision, accuracy and using grid search method to optimize fit parameters.

por Harshit R

8 de ago de 2020

Some Statistical terms and concepts were covered quite briefly due to which some amateur student has to refer additional contents like Youtube. Same with me. Quizes can be made tougher to raise the bar.

por Chuxuan Z

3 de abr de 2022

pros:very easy to understand, even the statistics knowledge

cons: incomplete python sentences in the video require extra efforts to undertand, such as no previous sentenses for an object (i.e. x_data)

por Sule C

12 de ago de 2020

Thank you very much to the instructors. I liked the course but it could have been better designed. More exercises ascending from easy to hard & real and teaching quiz questions would make it perfect.

por Roberto M

10 de jun de 2020

Great course to learn the basics for Data Analytics using Python.

I really liked the framework and data analysis template or process given in the labs. I will use them as a reference for my real job!

por Brijesh D

23 de nov de 2019

Really interesting course, if one wants learn programming language. Well designed and structured. Only suggestion is, if the small videos contains example that be really great to understand it well

por Luis M

10 de mar de 2020

Very good course that goes straight to the main topics needed to work on data analysis using Python. This will kick start my learning process which will be followed with a lot of coding practices.

por Cassie T

14 de mai de 2021

Good course, sometimes moves a bit fast in the final modules and the labs are quite tough but great course and would recommend to broaden your knowledge of coding, data analysis and visualisation

por Bharat M

16 de jul de 2020

Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should.

A good starter course to wet your feet in DA!

por wangqiucheng

7 de abr de 2020

Very clear and easy to learn. The lab helps a lot, it gives me an intuitive instruction of the class. But some of the points seem too shallow, hope the course could provide some deep knowledge.

por Mark W

12 de nov de 2021

Good Course. Very good overview of Python libs -Pandas, Numpy, Matplotlib, Scipy, Scikitlearn and Seaborn. I really enjoyed learning about them and seeing the usage. Highly recommended course.

por Nikhil D

31 de jul de 2021

T​otally overwhelmed with the course contents and easyness in teaching. The course will make you familiarize the fundamentals in a way that you will never forget when you used in a real world.

por rahi j

17 de out de 2018

It will be helpful if a video is added on:

1) how to store multiple results from different models in single dataframe

2) how to automate the process. More example needed on Grid and Pipeline.

por Rodrigo D

24 de fev de 2019

Great course, you can understand in a general way the use os Python to analyse raw data and organice it to create a better model. However I couldn't use in a proper way the external tool.

por Mason C

28 de abr de 2020

Theory and examples are good. Suggest having full and complete Python course code with more examples of each coding. So we can get more ideas and understanding of the Python environment.

por NAPA S M

7 de mai de 2019

Questions while listening to lessons in some of the lectures are coming before theory explained by the teacher .Better if question is at least 10 seconds after related theory explained.

por Cristian A M L

17 de fev de 2020

Los temas tratados son muy útiles y se desarrollan de gran manera. El herramienta de LAB es la más completa del curso. Considero que se puede aumentar la rigurosidad de la evaluación

por Daniel A

31 de mai de 2019

This was pretty good, I think maybe the best in the IBM machine learning certificate. I took Andrew Ng's course prior to this, so to watch python sklearn in action was a real treat.

por SHALINI G

1 de out de 2018

It is a good course for beginners but I feel that the quizzes could have been a bit more challenging. And if the codes were executed in the Python domain , it would have been nice.

por Charles R

9 de jan de 2021

Everything felt just a little too easy. I have minimal Python skills and nearly failed college statistics, but I never had any trouble here. The exercise notebooks were fantastic!