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Programa de cursos integrados Building Cloud Computing Solutions at Scale
Launch Your Career in Cloud Computing. Master strategies and tools to become proficient in developing data science and machine learning solutions in the Cloud
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O que você vai aprender
Build websites involving serverless technology and virtual machines, using the best practices of DevOps
Create Microservices using technologies like Flask and Kubernetes that are continuously deployed to a Cloud platform: AWS, Azure or GCP
Apply Machine Learning Engineering to build a Flask web application that serves out Machine Learning predictions
Habilidades que você terá
Sobre este Programa de cursos integrados
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With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find. This Specialization is designed to address the Cloud talent gap by providing training to anyone interested in developing the job-ready, pragmatic skills needed for careers that leverage Cloud-native technologies.
In the first course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines, using the best practices of DevOps. The second course will teach you how to build effective Microservices using technologies like Flask and Kubernetes that are continuously deployed to a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP). The third course begins to put together all of the Cloud concepts introduced in the first two courses to tackle more complex data engineering solutions. And finally, in the fourth course you will apply Machine Learning Engineering to build a Flask web application that serves out Machine Learning predictions.
Projeto de Aprendizagem Aplicada
Each course concludes with a real-world project where you have an opportunity to build a Cloud-native solution. For each Cloud solution that you develop, you will also create a demo video and GitHub repository of code that can be showcased in your digital portfolio for employers. By the end of this Specialization, you will be well-equipped to begin designing Cloud-native data engineering and machine learning solutions.
Certificados compartilháveis
Tenha o certificado após a conclusão
Cursos 100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Cronograma flexível
Definição e manutenção de prazos flexíveis.
Nível intermediário
Students should have beginner level Linux and intermediate level Python skills.
Aproximadamente 4 meses para ser concluído
Ritmo sugerido de 4 horas/semana
Inglês
Legendas: Inglês
Certificados compartilháveis
Tenha o certificado após a conclusão
Cursos 100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Cronograma flexível
Definição e manutenção de prazos flexíveis.
Nível intermediário
Students should have beginner level Linux and intermediate level Python skills.
Aproximadamente 4 meses para ser concluído
Ritmo sugerido de 4 horas/semana
Inglês
Legendas: Inglês
Como funciona o programa de cursos integrados
Fazer cursos
Um programa de cursos integrados do Coursera é uma série de cursos para ajudá-lo a dominar uma habilidade. Primeiramente, inscreva-se no programa de cursos integrados diretamente, ou avalie a lista de cursos e escolha por qual você gostaria de começar. Ao se inscrever em um curso que faz parte de um programa de cursos integrados, você é automaticamente inscrito em todo o programa de cursos integrados. É possível concluir apenas um curso — você pode pausar a sua aprendizagem ou cancelar a sua assinatura a qualquer momento. Visite o seu painel de aprendiz para controlar suas inscrições em cursos e progresso.
Projeto prático
Todos os programas de cursos integrados incluem um projeto prático. Você precisará completar com êxito o(s) projeto(s) para concluir o programa de cursos integrados e obter o seu certificado. Se o programa de cursos integrados incluir um curso separado para o projeto prático, você precisará completar todos os outros cursos antes de iniciá-lo.
Obtenha um certificado
Ao concluir todos os cursos e completar o projeto prático, você obterá um certificado que pode ser compartilhado com potenciais empregadores e com sua rede profissional.
Este Programa de cursos integrados contém 4 cursos
Cloud Computing Foundations
43 classificações
Welcome to the first course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines. You will also learn how to apply Agile software development techniques to projects which will be useful in building portfolio projects and global-scale Cloud infrastructures.
Cloud Virtualization, Containers and APIs
15 classificações
Welcome to the second course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn to design Cloud-native systems with the fundamental building blocks of Cloud computing. These building blocks include virtual machines and containers. You will also learn how to build effective Microservices using technologies like Flask and Kubernetes. Finally, you will analyze successful patterns in Operations including: Effective alerts, load testing and Kaizen.
Cloud Data Engineering
12 classificações
Welcome to the third course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to apply Data Engineering to real-world projects using the Cloud computing concepts introduced in the first two courses of this series. By the end of this course, you will be able to develop Data Engineering applications and use software development best practices to create data engineering applications. These will include continuous deployment, code quality tools, logging, instrumentation and monitoring. Finally, you will use Cloud-native technologies to tackle complex data engineering solutions.
Cloud Machine Learning Engineering and MLOps
11 classificações
Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone. Finally, you will dive into emerging topics in Machine Learning including MLOps, Edge Machine Learning and AI APIs.
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Universidade Duke
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Perguntas Frequentes – FAQ
Vou ganhar créditos universitários por concluir a Especialização?
Can I just enroll in a single course?
Posso me inscrever em um único curso?
Existe algum auxílio financeiro disponível?
Posso fazer o curso gratuitamente?
Este curso é realmente 100% on-line? Eu preciso assistir alguma aula pessoalmente?
How long does it take to complete the Specialization?
Quanto tempo é necessário para concluir a Especialização?
Do I need to take the courses in a specific order?
Will I receive a transcript from Duke University for completing this course?
Will I earn university credit for completing the Specialization?
Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.
