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Trabalho de conclusão de Ciência de Dados Aplicada

Alex Aklson
Este curso do projeto de conclusão mostrará um pouco do que os cientistas de dados passam na vida real ao trabalhar com dados. Você aprenderá sobre dados de localização e diferentes provedores de dados de localização, como o Foursquare. Você aprenderá como...
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Este curso do projeto de conclusão mostrará um pouco do que os cientistas de dados passam na vida real ao trabalhar com dados. Você aprenderá sobre dados de localização e diferentes provedores de dados de localização, como o Foursquare. Você aprenderá como fazer chamadas de API RESTful para a API do Foursquare a fim de recuperar dados sobre locais em diferentes bairros do mundo. Você também aprenderá como usar a criatividade quando os dados não estiverem disponíveis na hora, coletando dados da Web e analisando o código HTML. Você utilizará Python e sua biblioteca do Pandas para manipular dados, o que ajudará você a refinar suas habilidades para explorar e analisar dados. Por fim, você deverá usar a biblioteca Folium para obter excelentes mapas de dados geoespaciais e para comunicar seus resultados e descobertas. Se optar por fazer este curso e obter o certificado de conclusão de curso do Coursera, você também poderá ganhar um selo digital da IBM. OFERTA LIMITADA: a assinatura custa apenas US$ 39,00 por mês para acesso a materiais classificados e a um certificado.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides hands-on learning through data manipulation and visualization
Involves collecting data from real-world sources like the Foursquare API
Teaches practical skills in data analysis and visualization using Python and its libraries
Requires students to have some experience in Python and data analysis
May require additional resources to supplement the course materials
The curriculum is focused on a specific aspect of data analysis: geospatial data

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Activities

Coming soon We're preparing activities for Trabalho de conclusão de Ciência de Dados Aplicada. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Trabalho de conclusão de Ciência de Dados Aplicada will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists are experts in collecting, cleaning, and analyzing data to extract insights and inform decision-making. This course provides a foundation for this career by teaching you how to work with location data, make API calls, and use Python and Pandas for data manipulation. You'll also learn how to present your findings through interactive maps using the Folium library.
Data Analyst
Data Analysts use data to solve business problems and improve decision-making. This course provides a strong foundation for this role by teaching you how to collect, clean, and analyze data. You'll also learn how to use Python and Pandas for data manipulation and Folium for creating interactive data visualizations.
Data Engineer
Data Engineers design and build the systems that store, process, and analyze data. This course provides a foundation for this role by teaching you how to work with data in the cloud, use Python for data manipulation, and create data pipelines.
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models to solve real-world problems. This course provides a foundation for this role by teaching you how to collect, clean, and analyze data, use Python for data manipulation, and build machine learning models.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful for this role by teaching you how to use Python for data manipulation and how to create interactive data visualizations.
Web Developer
Web Developers design and develop websites and web applications. This course may be useful for this role by teaching you how to make API calls and how to create interactive data visualizations.
Business Analyst
Business Analysts use data to understand business problems and improve decision-making. This course provides a foundation for this role by teaching you how to collect, clean, and analyze data. You'll also learn how to use Python for data manipulation and Folium for creating interactive data visualizations.
Project Manager
Project Managers plan, execute, and deliver projects. This course may be useful for this role by teaching you how to manage data-driven projects and how to communicate your findings effectively.
Product Manager
Product Managers are responsible for the development and launch of new products. This course may be useful for this role by teaching you how to collect and analyze data to understand customer needs.
Marketing Manager
Marketing Managers plan and execute marketing campaigns to promote products and services. This course may be useful for this role by teaching you how to collect and analyze data to understand customer behavior.
Sales Manager
Sales Managers lead sales teams and are responsible for achieving sales goals. This course may be useful for this role by teaching you how to collect and analyze data to understand customer needs and trends.
Operations Manager
Operations Managers are responsible for the day-to-day operations of a business. This course may be useful for this role by teaching you how to collect and analyze data to improve efficiency and productivity.
Financial Analyst
Financial Analysts provide financial advice to individuals and organizations. This course may be useful for this role by teaching you how to collect and analyze data to make informed investment decisions.
Consultant
Consultants provide advice and guidance to businesses and organizations. This course may be useful for this role by teaching you how to collect and analyze data to help clients solve problems and make informed decisions.
Teacher
Teachers educate students at all levels. This course may be useful for this role by providing you with a foundation in data science that you can share with your students.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Trabalho de conclusão de Ciência de Dados Aplicada.
Discusses graphs and charts in detail, including their practical uses, and is an excellent reference tool for data scientists.
Serves as a practical guide to the field of data science and its applications, serving as a helpful introduction to the field.
Serves as a Python-based introduction to the field of machine learning, covering basic concepts and techniques.
Discusses the challenges and pitfalls of data science and provides practical advice for navigating them.

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