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

4.7
estrelas
8,579 classificações
1,123 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

Apr 20, 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.

AB

Feb 13, 2020

Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.

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1001 — 1025 de {totalReviews} Avaliações para o Análise de dados com Python

por Marc T

Feb 03, 2020

why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

por Abhishek K

Aug 26, 2019

Model creation and analysis part are too short, should have more details to understand the concepts better.

por Sarah s

Jan 02, 2019

This course seems to have an exponential increase in a learning curve. It seemed to be all over the place.

por Ramakrishna B

Jun 19, 2019

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections

por Kenneth S

Jan 13, 2020

As always, the final project always ruins good courses. LAZY design of the projects is unacceptable.

por Bjoern K

Jun 14, 2019

Week 4 is somewhat hard to follow - Here, an overview over the different concepts would really help

por Nadeesha J S

Apr 11, 2019

I would like to see a final project in this course. It will encourage the learners to do more work.

por Nathan P

Jan 02, 2020

It was cool to see the stuff at work but I need more hands on practice to really learn stuff.

por Varun V

Dec 19, 2018

This looks good for experienced but not the best of course for beginners/intermediate level.

por Connor F

Mar 28, 2020

when it got to model development it got too complicated too fast. The first half was great.

por BT

May 28, 2019

Lots of good concepts. However, too complicated and could have been explained a bit more.

por Jesse Z

Jun 05, 2019

For such a important topic, it seems like the videos sped through some essential topics.

por Debra C

Mar 24, 2019

Course was worthwhile for general understanding of what can be accomplished with Python.

por Chau N N H

Jan 29, 2020

The lesson need more explanations on Polynomial Regression, Pipeline, Ridge Regression.

por Xinyi W

Jan 26, 2020

Superfacial level of Python while being not very through on the data analysis methods.

por Ana C

Jun 11, 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course

por Sathiya P

Aug 27, 2019

Nicely thought, but I felt concepts like Decision trees, Random forest were missing

por Rosana R M

Aug 13, 2019

The course is too long. The material should be divided and explained more detailed.

por Maciej L

May 16, 2019

Too many complicated things happening at once. It is hard to digest and follow.

por Tomasz S

Nov 19, 2018

Few small hiccups with the training videos and quite a few in the lab-excercise

por Pierre-Antoine M

Feb 19, 2020

Videos are nice but they are mistakes in the notebooks that disturbs learning

por Toan N

Mar 27, 2020

The lab is disconnected every so often that can't complete it smoothly.

por Jessica B

Jun 14, 2019

Good content, but lots of typos. The outsourcing is extremely evident.

por Arjun S C

Aug 14, 2019

Lots of bugs and errors. No instructors reply on the discussion forum.

por Filippo M

Sep 27, 2019

Useful course, but the IBM online platforms are not working well.