Voltar para Análise de dados com Python

4.7

estrelas

8,768 classificações

•

1,162 avaliações

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....

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.

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.

Filtrar por:

por Dr M S A

•Nov 20, 2019

It was a very interesting and correctly paced course for learning Data Analysis with Python. The course content and the assignments were very helpful in understanding the course well. Will recommend this course to all who want to do a well paced introductory course on Data Analytics using Python

por Md. R H

•Sep 22, 2019

This course is outstanding valuable for the beginners who wants to build their career as data analysist. I have learned a lots of valuable statistical and progrmming for data analysis. Thanks to all instructor to give us such a opportunity to learn such kind of code and method for data analysis.

por Jamiil T A

•Jan 02, 2019

Awesome. A must take course very handy at giving the foundation of data analysis with python and what a nice introduction to linear regression with the library sklearn. For more it looks more like an in-depth course in linear regression. Kudos, the explanations of concepts were well approached.

por Md. A A J

•Apr 04, 2020

The hands on examples for practicing on IBM cognitive lab, videos and lecturers made are great and helpful. The course contents are clear, precise and lecturer is very knowledgeable.

Joining and getting help from course mates and moderates in discussion forum is Excellent!

Ashfaque A. Joarder

_{}^{}

por Konstantin D

•Feb 23, 2019

The first "week" was way too simple. I believe things like "what a file path is" should belong to another course. The last 4 "weeks" gave a good picture of where to start with data analysis. The whole course can be completed after 5-10 hours (depends how long you play with the dev tool).

por Surhan Z

•Jun 15, 2019

This course core purpose is to teach the student how to perform analysis in detail. I have taken a lot of courses related to data analysis but no one teaches in detail and gives great examples. I highly recommend this course to all student who wants to learn data analysis with python.

por Vera C

•Jan 16, 2020

This course is actually harder than expected due to the python programming however I felt I truly benefited from it. I have learned and used Python before, but the python code in this course sets a new high bar for me. I'm going to go back and study all the labs in this course again!

por Ketan K

•Dec 28, 2018

Really a step up in terms of difficulty compared to "Data Science with Python". Since the final week's content is judged on quiz and not a stand alone assignment, one must revise this course from time to time for the libraries referenced and model analysis approach. Great resource!

por Gajula J

•Jul 16, 2018

This course is very good start for students who are planning to go into machine learning specifically.Students who have no Idea about regression and math find bit hard but little more effort from student side is needed. At the end you will have a zeroth tool for machine learning.

por Jason J D

•Sep 12, 2019

Really good course in Data Analysis for beginners. The videos and labs are very well planned and structured. Personally, I can say for sure that I have gained more knowledge about Data Analysis and am even more motivated towards Data Science after completing this course.

por SUSHANT

•Apr 07, 2019

This course give a great introduction to the Python Packages and methodology to visualize the data and also evaluate the Model. This is good introduction course which gives concise understanding of concepts and all important python libraries required to get the job done.

por Javed A

•Oct 20, 2019

What an amazing way to learn such a special set of skills from best platform of Coursera.

The IBM Skills Network Lab is really fantastic.

Also on IBM studio is speechless.

I will definitely recommend this must have course to all passionate learners around the globe.

por Kuldeep N P

•Jul 13, 2018

Help to understand the process of doing projects on Data Science , As i tried to start with one Data set but i was not sure what to do, how to do. with the help of this course, I came to know the step by step process of Data Wrangling and making models. Thanks

por Sagar S

•Sep 17, 2018

This is very condense course. However the quizzes after every chapter are very timely, and one at the end of the week for entire week, helped a lot. The labs seems very real world, downloaded some notebook am sure will be using them in real world later on.

por Abdulahi O F

•Aug 21, 2019

I am highly impressed with the teaching methodologies and how the course is structured. By now, I can import, determine data types, conduct data wrangling which involves replacement ir dropping and regressions. Thanks to Cousera for the opportunity.

por Luciana M G

•Mar 14, 2019

This course is an excellent continuation of the previous IBM ones. Actually there should be one whole course teaching the basics of statistics so that what is taught in this model makes more sense for those who have never studied statistics before.

por Guy B

•Sep 24, 2019

Great course. few things to make it perfect:

more mathematic explanations required.

more details and explanations about the code itself - the methods and the opportunities inside it.

make the videos more interesting and not so monotonic and boring.

por mustapha b

•Jan 06, 2020

I thank Mr. Joe Santarcangelo 🙏🏼 who helped me learn how to prepare data for hashtag#analysis, perform simple hashtag#statistical analysis, create meaningful hashtag#data visualizations and hashtag#predict future trends from the data👨🏼💻.

por Mike F

•Oct 18, 2019

Outstanding course! Valuable information and methodologies all with clear and concise presentation. The labs are detailed and filled with awesome examples. Coursework is intuitive and easy to understand. I would highly recommend this course.

por Ricardo S

•Feb 25, 2020

La calidad de los cursos de coursera es excelente. Obviamente tienen detalles que se deben trabajar como algunas presentaciones que no coinciden con las voces en off. Sin embargo con suspicacia se pueden solventar estos infimos detalles.

por Jafed E

•Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

por QUAN Z

•Feb 26, 2019

The course perfectly fits those who has some knowledge on python and want to do data analysis with it. It explains how professionals would process data, build model with the data, and use the model to solve a real problem.

por Jonathan I O

•Jul 15, 2019

This course provides a robust walk-through in the use of python for data analysis. The labs ensure the theories taught are put into practice through hands-on projects that further reinforces skills learned. I loved it!

por Aman S

•Mar 26, 2020

A very detailed course. The hands-on exercises were really good and I got to learn a lot of things from this wonderful course. Thanks to all the instructors for their hard work in putting together such a course for us.

por Ferenc F P

•Feb 26, 2019

The beginning of the course helps you understanding how you can manage your data with python. In the end linear regression, and ridge regression is also introduced. Good course for those not familiar in this field.

- IA para todos
- Introdução ao TensorFlow
- Redes neurais e aprendizagem profunda
- Algoritmos, parte 1
- Algoritmos, parte 2
- Aprendizagem Automática
- Aprendizagem automática com Python
- Aprendizagem automática usando o Sas Viya
- Linguagem R
- Introdução à programação com Matlab
- Análise de dados com Python
- Fundamentos da AWS: Going Cloud Native
- Fundamentos da Google Cloud Platform
- Engenharia de confiabilidade do site
- Fale inglês profissionalmente
- A ciência do bem-estar
- Aprendendo a Aprender
- Mercados Financeiros
- Testes de hipóteses em saúde pública
- Princípios da liderança no cotidiano

- Aprendizagem profunda
- Python para todosPython para todos
- Ciência de Dados
- Ciência de dados aplicada com Python
- Fundamentos de negóciosFundamentos dos Negócios
- Arquitetura com o Google Cloud Platform
- Engenharia de dados em Google Cloud Platform
- Excel para MySQL
- Aprendizagem de máquina avançada
- Matemática para aprendizagem automática
- Carros autoguiáveis
- Revolução do Blockchain para a empresa
- Análises empresariaisAnálises Empresariais
- Habilidades em Excel para negócios
- Marketing digitalMarketing Digital
- Análise estatística com R para saúde pública
- Fundamentos da imunologia
- Anatomia
- Gestão da inovação e Design Thinking
- Princípios da psicologia positiva