DevOps for Data Scientists: Data Science DevOps
DevOps
| Intermediate
- 16 Videos | 1h 19m 26s
- Includes Assessment
- Earns a Badge
In this 16-video course, learners discover the steps involved in applying DevOps to data science, including integration, packings, deployment, monitoring, and logging. You will begin by learning how to install a Cookiecutter project for data science, then look at its structure, and discover how to modify a Cookiecutter project to train and test a model. Examine the steps in the data model lifecycle and the benefits of version control for data science. Explore the tools and approaches to continuous integration for data models, to data and model security for Data DevOps, and the approaches to automated model testing for Data DevOps. Learn about the Data DevOps considerations for data science tools and IDEs (integrated developer environment) and the approaches to monitoring data models and logging for data models. You will examine ways to measure model performance in production and look at data integration with Cookiecutter. Then learn how to implement a data integration task with both Jenkins and Travis CI (continuous integration). The concluding exercise involves implementing a Cookiecutter project.
WHAT YOU WILL LEARN
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discover the subject areas covered in this course
examine a Cookiecutter project structure
modify a Cookiecutter project to train and test a model
describe the steps in the data model life cycle
describe the benefits of version control for data science
describe tools and approaches to continuous integration for data models
describe approaches to data and model security for Data DevOps
describe approaches to automated model testing for Data DevOps -
identify Data DevOps considerations for data science tools and IDEs
identify approaches to monitoring data models
describe approaches to logging for data models
identify ways to measure model performance in production
add directives to the make file to prepare for continuous integration
implement a data integration task with Jenkins
implement data integration with Travis CI
incorporate a model into a Cookiecutter project
IN THIS COURSE
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1.Course Overview1m 22sUP NEXT
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2.Cookiecutter Project Structure7m 36s
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3.Using a Cookiecutter Project6m 47s
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4.Data Model Life Cycle5m 4s
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5.Version Control in Data Science3m 56s
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6.Data Model Continuous Integration3m 47s
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7.Data and Model Security5m 3s
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8.Automated Model Testing4m 10s
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9.Data Tools in DevOps4m 46s
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10.Monitoring Data Models3m 4s
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11.Logging for Data Models2m 49s
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12.Model Performance Measures4m 33s
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13.Data Integration with Cookiecutter5m 22s
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14.Data Integration with Jenkins4m 46s
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15.Data Integration with Travis CI4m 24s
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16.Exercise: Implement a Cookiecutter Project4m 59s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion of this course, which can be shared on any social network or business platform
Digital badges are yours to keep, forever.
