Cientista de dados associado em Python

Aprenda Python para ciência de dados e adquira as habilidades de construção de carreira que você precisa para ter sucesso como cientista de dados, desde a manipulação de dados até o aprendizado de máquina! Neste curso, você aprenderá como essa linguagem versátil permite importar, limpar, manipular e visualizar dados - todas habilidades essenciais para qualquer aspirante a profissional ou pesquisador de dados. Começando com os fundamentos do Python para a ciência de dados, você trabalhará com exercícios interativos que testarão suas habilidades. Você terá contato prático com algumas das bibliotecas Python mais populares para ciência de dados, incluindo pandas, Seaborn, Matplotlib, scikit-learn e muitas outras. À medida que progredir, você trabalhará com conjuntos de dados do mundo real para aprender as técnicas estatísticas e de aprendizado de máquina necessárias para realizar testes de hipóteses e criar modelos preditivos. Você também terá uma introdução ao aprendizado supervisionado com o scikit-learn e aplicará suas habilidades em vários projetos. Comece este curso, desenvolva suas habilidades em ciência de dados e inicie sua jornada para passar com confiança na certificação Associate Data Scientist in Python e prosperar como cientista de dados.

Python86 horas22 courses11 projectsDeclaração de Realização

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Introdução ao Python

4 hours

Python intermediário

4 hours

Investigating Netflix Movies

Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie data.

2 hours

Manipulação de dados com pandas

4 hours

Exploring NYC Public School Test Result Scores

Use data manipulation and summary statistics to analyze test scores across New York City's public schools!

2 hours

Joining Data with pandas

Learn to combine data from multiple tables by joining data together using pandas.

4 hours

Introduction to Statistics in Python

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

4 hours

Introduction to Data Visualization with Matplotlib

Learn how to create, customize, and share data visualizations using Matplotlib.

4 hours

Introduction to Data Visualization with Seaborn

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

4 hours

Visualizing the History of Nobel Prize Winners

Explore a dataset containing a century's worth of Nobel Laureates. Who won? Who got snubbed?

2 hours

Python Data Science Toolbox (Part 1)

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

3 hours

Python Data Science Toolbox (Part 2)

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

4 hours

Data Manipulation with Python

Exploratory Data Analysis in Python

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

4 hours

Analyzing Crime in Los Angeles

Find out when and where crime is most likely to occur, along with the types of crimes commonly committed in LA.

2 hours

Working with Categorical Data in Python

Learn how to manipulate and visualize categorical data using pandas and seaborn.

4 hours

Customer Analytics: Preparing Data for Modeling

Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!

2 hours

Data Communication Concepts

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

3 hours

Introduction to Importing Data in Python

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

3 hours

Cleaning Data in Python

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hours

Exploring Airbnb Market Trends

Apply your data importing, cleaning and manipulation skills to explore New York City Airbnb data.

2 hours

Working with Dates and Times in Python

Learn how to work with dates and times in Python.

4 hours

Importing & Cleaning Data with Python

Writing Functions in Python

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

4 hours

Python Programming

Introduction to Regression with statsmodels in Python

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

4 hours

Modeling Car Insurance Claim Outcomes

Clean customer data and use logistic regression to predict whether people will make a claim on their car insurance!

2 hours

Sampling in Python

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

4 hours

Hypothesis Testing in Python

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

4 hours

Hypothesis Testing with Men's and Women's Soccer Matches

Perform a hypothesis test to determine if more goals are scored in women's soccer matches than men's!

2 hours

Aprendizagem supervisionada com o scikit-learn

4 hours

Predictive Modeling for Agriculture

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.

2 hours

Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hours

Clustering Antarctic Penguin Species

Arctic Penguin Exploration: Unraveling Clusters in the Icy Domain with K-means Clustering

2 hours

Machine Learning with Tree-Based Models in Python

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hours

Predicting Movie Rental Durations

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

2 hours

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Principais avaliações

Wilfrido O.

6 months

This career track has everything need for data science! I

Imre L.

8 months

OK.

Muhammad A.

9 months

I have taken the previous version of the course as well. I think that may be more alligned to theory, the newer version is more suitable for newbies. Overall, it's a good addition. However, the significane of the subject requires more and more practice on these topics so that a student can be master on these.

Aldo V.

22 days

Courses are great and give you a great follow through, what I think could help more is having a more complete exercise at the end of each course that requires you to code everything and not just fill the blank spaces

Maciej G.

about 1 month

Well created skill track, that took me round 2 years to finish. Good quality materials, test, task and perfect bright teachers.

"This career track has everything need for data science! I"

Wilfrido O.

"OK."

Imre L.

"I have taken the previous version of the course as well. I think that may be more alligned to theory, the newer version is more suitable for newbies. Overall, it's a good addition. However, the significane of the subject requires more and more practice on these topics so that a student can be master on these."

Muhammad A.

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Cadastre-se mais .css-ou6dz6{color:#03ef62;}13,700,000 Alunos e comece Cientista de dados associado em Python Hoje!

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Training 2 or more people?

Cadastre-se mais 13,700,000 Alunos e comece Cientista de dados associado em Python Hoje!