From DevOps to MLOps: Enabling Artificial Intelligence
summary
Covers how combining DevOps practices with MLOps enables end-to-end automation of the AI model lifecycle—development, deployment, and continuous monitoring—while ensuring model reusability and governance in agile teams, and leveraging cloud scalability and elasticity to run high-performance AI solutions.
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chapters (10)
- 0:00Introduction
- 1:05DevOps to new roles
- 2:33FinOps and DataOps
- 4:45DevOps to MLOps
- 6:13ML maturity
- 10:25MLOps skills
- 16:33Technical knowledge
- 18:21Personal MLOps transition
- 20:31MLOps role
- 22:14Observability
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