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.

Big Data: Técnicas e Aplicações

O Big Data é um conjunto de metodologias utilizadas para capturar, armazenar e processar esse grande volume de informações que podem vir de várias fontes e tem como o objetivo principal acelerar a tomada de decisão e facilitar a vida das pessoas e empresas que precisam analisar informações. E por que o Big Data é tão importante? Para empresas, processar informações de forma rápida e precisa, pode garantir a sobrevivência em um mercado tão competitivo. Portanto, ter acesso a informação, realizar análises e extrair ideias para a sua estratégia, pode ser um grande diferencial para alavancar sua estratégia de vendas.

Mineração de Dados: Técnicas e Aplicações

A mineração de dados é o processo utilizado para encontrar anomalias, padrões e correlações em grandes conjuntos de dados para prever tendências e resultados significativos, esse processo nos ajuda a tomar decisões, reduzir riscos, identificar problemas e soluções para esses problemas, entre outras funções importantes para a evolução de uma empresa.A mineração de dados não se resume a apenas tecnologia, pois é necessário conhecimento aprofundado de negócios para se definir uma estratégia de análise e definir caminhos para a correta tomada de decisão. Este módulo apresenta as principais técnicas para a coleta e estruturação dos dados.

Cultura Orientada a Dados nas Organizações

Uma empresa data driven é uma empresa que utiliza processos orientados por dados, ou seja, toda e qualquer decisão é embasada na coleta, processamento e análise da informação. Isso significa utilizar os dados como base para a tomada de decisão e do planejamento estratégico, buscando métodos confiáveis ao invés de direcionar as ações baseadas em intuição.

Good to know

Know what's good

, what to watch for

, 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

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:

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 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.

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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.

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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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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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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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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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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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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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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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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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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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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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