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.
Este curso faz parte do Programa de cursos integrados Building Cloud Computing Solutions at Scale
oferecido por
Informações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Beginner level Linux and Python skills
Aprox. 12 horas para completar
Inglês
Legendas: Inglês
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Beginner level Linux and Python skills
Aprox. 12 horas para completar
Inglês
Legendas: Inglês
oferecido por
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.
Programa - O que você aprenderá com este curso
4 horas para concluir
Getting Started with Machine Learning Engineering
This week, you will learn about the methodologies involved in Machine Learning Engineering. By the end of the week, you will be able to develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications.
4 horas para concluir
15 vídeos (Total 47 mín.), 5 leituras, 1 teste
4 horas para concluir
Using AutoML
This week, you will learn about AutoML and how to use it to build efficient Machine Learning solutions with little to no code. These technologies include Ludwig, Google AutoML, Apple Create ML and Azure Machine Learning Studio. You will apply these solutions by using both open source and Cloud AutoML technology.
4 horas para concluir
21 vídeos (Total 138 mín.), 2 leituras, 1 teste
5 horas para concluir
Emerging Topics in Machine Learning
This week, you will learn MLOps strategies and best practices in designing Cloud solutions. Then, you will explore Edge Machine Learning and how to use AI APIs. You will apply these strategies to build a low code or no code Cloud solution that performs Natural Language Processing or Computer Vision.
5 horas para concluir
22 vídeos (Total 158 mín.), 2 leituras, 1 teste
Avaliações
Principais avaliações do CLOUD MACHINE LEARNING ENGINEERING AND MLOPS
por SG8 de Jul de 2021
Excellent course, very concise but complete, if possible a second version would be ideal
Sobre Programa de cursos integrados Building Cloud Computing Solutions at Scale
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.
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