Introdução à Ciência e Engenharia de Dados from Coursera

Neste curso, você aprenderá que os dados se tornaram o principal ativo de negócios nos dias de hoje. Com o aumento do Big Data e criação de novas tecnologias, as organizações em todo o mundo estão inovando e descobrindo novas formas para analisar o potencial dos dados à sua disposição, o que ajuda no crescimento, na lucratividade, no direcionamento das operações gerais e no aumento da satisfação do cliente. Mas para que tudo isso funcione corretamente e seja possível extrair todo o potencial de forma precisa e que seja viável para o negócio, criou-se a área de ciência de dados.

Ao final deste curso, você será capaz de compreender todo o processo de ciência de dados e o uso da tecnologia em um mundo conectado, entender todo o escopo de ciência e engenharia de dados e conhecer as principais metodologias de projeto para ciência de dados.

Este curso é composto por quatro módulos, disponibilizados em semanas de aprendizagem. Cada módulo é composto por vídeos, leituras e testes de verificação de aprendizagem. Ao final de cada módulo, temos uma avaliação de verificação dos conhecimentos.

Estamos muito felizes com sua presença neste curso e esperamos que você tire o máximo de proveito dos conceitos aqui apresentados.

Bons estudos!

What's inside

Syllabus

Ciência de Dados para Tomada de Decisão

A Ciência de dados é uma combinação de vários campos que envolvem a utilização de dados para a resolução de problemas complexos, como tecnologia, desenvolvimento de algoritmos e inferência estatística para estudar os dados, analisá-los e encontrar soluções inovadoras para os problemas difíceis. A área de ciência de dados possui três áreas principais de especialização - Matemática, Domínio de Negócios e Tecnologia.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Ajuda você a compreender o processo de ciência de dados e o uso da tecnologia

Abrange técnicas para coleta e estruturação de dados

Ensina sobre Big Data e suas aplicações

Apresenta a mineração de dados e seus benefícios

Discute a importância de uma cultura orientada a dados nas organizações

Reviews summary

Fundamentos essenciais em ciência de dados

Segundo os alunos, este curso é uma excelente porta de entrada (positive) para o universo da ciência e engenharia de dados (neutral), oferecendo uma visão abrangente e acessível (positive) sobre o tema. Muitos destacam a clareza dos conceitos (positive) e o foco na aplicação para tomada de decisão (positive), tornando-o ideal para iniciantes (positive) ou profissionais que buscam entender o papel estratégico dos dados. Embora proporcione uma base sólida (positive), alguns comentam que o conteúdo é essencialmente teórico (warning) e poderia se beneficiar de mais exemplos práticos ou ferramentas específicas (warning), sendo menos adequado para quem busca aprofundamento técnico imediato (warning).

Enfatiza a importância dos dados para decisões estratégicas.

"Gostei muito de como o curso conecta a ciência de dados diretamente com as estratégias empresariais."

"A parte sobre cultura orientada a dados foi muito relevante para minha atuação profissional."

"Entendi perfeitamente como os dados podem ser um ativo crucial para qualquer empresa."

Estrutura didática acessível para quem está começando.

"Perfeito para quem nunca teve contato com a área, as explicações são muito didáticas."

"Senti que a linguagem utilizada é muito amigável para leigos, facilitando o aprendizado."

"Mesmo sem background em TI, consegui acompanhar e compreender todos os tópicos."

Apresenta os conceitos essenciais de forma ampla.

"O curso me deu uma excelente introdução ao mundo da ciência de dados, cobrindo os fundamentos que eu precisava."

"Consegui ter uma visão clara do que é ciência e engenharia de dados e seu escopo geral."

"É uma ótima base para quem não tem conhecimento prévio e quer entender a área."

Requer estudos complementares para especialização.

"É um excelente ponto de partida, mas sei que preciso de outros cursos para me aprofundar nas técnicas."

"Se você busca se tornar um cientista de dados, este é só o primeiro passo, não o suficiente por si só."

"O curso abre a mente, mas para virar um especialista, a continuação dos estudos é crucial."

Prioriza conceitos sobre a prática com ferramentas.

"Embora seja uma boa introdução, senti falta de exemplos mais práticos ou exercícios de programação."

"O curso é ótimo para a teoria, mas não me preparou para usar softwares ou linguagens de dados."

"Para quem busca 'colocar a mão na massa', o conteúdo pode ser um pouco abstrato demais."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introdução à Ciência e Engenharia de Dados with these activities:

Revise basic probability theory

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Refresh your understanding of probability theory to prepare for this course's statistical concepts.

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Review definitions and concepts of probability
Practice solving probability problems

Connect with data science professionals

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Expand your professional network by seeking out mentors who can provide guidance and insights into the field of data science.

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Attend industry events and conferences
Join online communities and forums
Reach out to professionals in your field

Complete data analysis exercises

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Enhance your data analysis skills by practicing with exercises that cover techniques and concepts discussed in the course.

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Gather data from various sources
Clean and prepare the data
Apply data analysis techniques
Interpret and visualize the results

Four other activities

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Develop a data analysis presentation

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Enhance your communication skills by creating a presentation that showcases your ability to analyze and convey data insights effectively.

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Determine the purpose and audience of your presentation
Choose appropriate visualization techniques
Craft a clear and concise narrative
Rehearse and deliver your presentation

Build a data analysis portfolio

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Solidify your data analysis knowledge by working on a project that involves data collection, analysis, and presentation.

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Identify a problem or question to address
Collect and prepare the necessary data
Analyze the data using appropriate techniques
Present your findings and insights

Contribute to open-source data science projects

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Gain hands-on experience and contribute to the data science community by volunteering on open-source projects.

Browse courses on GitHub

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Find open-source projects that align with your interests
Identify areas where you can contribute
Submit code or documentation changes
Collaborate with other contributors

Participate in data science competitions

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Challenge yourself and gain practical experience by participating in data science competitions.

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Identify relevant competitions that align with your skills and interests
Form a team or work individually
Develop and implement data analysis solutions
Submit your results and receive feedback

Career center

Learners who complete Introdução à Ciência e Engenharia de Dados will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist designs, builds, and deploys algorithms to extract valuable information from data. This course can help you become a Data Scientist by providing you with a solid foundation in the fundamentals of data science, including data collection, analysis, and visualization. You will also learn about the different techniques used in data science, such as machine learning and statistical modeling.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst collects, analyzes, and interprets data to help businesses make better decisions. This course can help you become a Data Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use data visualization tools to communicate your findings to others.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

A Business Intelligence Analyst uses data to help businesses improve their operations. This course can help you become a Business Intelligence Analyst by providing you with the skills you need to collect, analyze, and interpret data. You will also learn how to use data visualization tools to communicate your findings to others.

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Data Engineer

A Data Engineer designs and builds the infrastructure that stores and processes data. This course can help you become a Data Engineer by providing you with the skills you need to design and build scalable data pipelines. You will also learn about the different technologies used in data engineering, such as Hadoop and Spark.

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Machine Learning Engineer

A Machine Learning Engineer designs and builds machine learning models. This course can help you become a Machine Learning Engineer by providing you with a solid foundation in the fundamentals of machine learning. You will also learn about the different techniques used in machine learning, such as supervised learning, unsupervised learning, and deep learning.

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Statistician

A Statistician collects, analyzes, and interprets data to help businesses make better decisions. This course can help you become a Statistician by providing you with a solid foundation in the fundamentals of statistics. You will also learn about the different techniques used in statistics, such as hypothesis testing and regression analysis.

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Software Engineer

A Software Engineer designs, builds, and tests software applications. This course can help you become a Software Engineer by providing you with a solid foundation in the fundamentals of software engineering. You will also learn about the different techniques used in software engineering, such as object-oriented programming and design patterns.

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Database Administrator

A Database Administrator designs and manages databases. This course can help you become a Database Administrator by providing you with the skills you need to design and manage scalable databases. You will also learn about the different technologies used in database administration, such as SQL and NoSQL.

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Marketing Analyst

A Marketing Analyst uses data to help businesses improve their marketing campaigns. This course can help you become a Marketing Analyst by providing you with the skills you need to collect, analyze, and interpret data. You will also learn about the different techniques used in marketing analytics, such as customer segmentation and market research.

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Financial Analyst

A Financial Analyst uses data to help businesses make better financial decisions. This course can help you become a Financial Analyst by providing you with the skills you need to collect, analyze, and interpret data. You will also learn about the different techniques used in financial analysis, such as financial modeling and valuation.

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Product Manager

A Product Manager designs and manages products. This course can help you become a Product Manager by providing you with the skills you need to understand the needs of your users and develop products that meet those needs. You will also learn about the different techniques used in product management, such as user research and product development.

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Project Manager

A Project Manager plans and manages projects. This course can help you become a Project Manager by providing you with the skills you need to plan and manage projects effectively. You will also learn about the different techniques used in project management, such as project planning and risk management.

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Business Analyst

A Business Analyst analyzes businesses and their operations to identify areas for improvement. This course can help you become a Business Analyst by providing you with the skills you need to analyze businesses and their operations. You will also learn about the different techniques used in business analysis, such as process mapping and data analysis.

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Operations Research Analyst

An Operations Research Analyst uses data to help businesses improve their operations. This course can help you become an Operations Research Analyst by providing you with the skills you need to collect, analyze, and interpret data. You will also learn about the different techniques used in operations research, such as linear programming and simulation.

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Supply Chain Analyst

A Supply Chain Analyst analyzes supply chains to identify areas for improvement. This course can help you become a Supply Chain Analyst by providing you with the skills you need to analyze supply chains. You will also learn about the different techniques used in supply chain analysis, such as network analysis and inventory management.

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