DevOps for Data Scientists
With Dan Sullivan
Liked by 1,134 users
Duration: 32m
Skill level: Intermediate
Released: 5/10/2018
Course details
Data scientists create data models that need to run in production environments. Many DevOps practices are relevant to production-oriented data science applications, but these practices are often overlooked in data science training. In addition, data science and machine learning have distinct requirements, such as the need to revise models while in use. This course was designed for data scientists who need to support their models in production, as well as for DevOps professionals who are tasked with supporting data science and machine learning applications. Learn about key data science development practices, including the testing and validation of data science models. This course also covers how to use the Predictive Model Markup Language (PMML), monitor models in production, work with Docker containers, and more.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
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Showcase on your LinkedIn profile under “Licenses and Certificate” section
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Meet the instructor
Learner reviews
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Jeba Schulz J
Jeba Schulz J
💻 Senior Systems Engineer @ EPAM Systems | Ex-Accenture | ♾️ DevOps | ☁ Cloud - Azure 5X ♦️ AWS 1X ♦️ GCP 1X ♦️ K8S 1X
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Contents
What’s included
- Test your knowledge 4 quizzes
- Learn on the go Access on tablet and phone
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