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Machine Learning Operations (MLOps): Getting Started
Google via Google Cloud Skills Boost
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Overview
This course covers foundational concepts in MLOps, the practice of managing ML modelsâ lifecycle in production. Learners study CI/CD pipelines, version control, monitoring, and automation strategies that enhance model reliability and scalability. Using popular tools and cloud services, participants will gain practical skills to implement MLOps workflows and improve AI system maintenance.
Syllabus
- Welcome to the Machine Learning Operations (MLOps): Getting Started
- Course introduction
- Employing Machine Learning Operations
- Introduction to MLOps-Why and when to employ MLOps
- Machine learning (ML) practitioners pain points
- The concept of devOps in ML
- ML lifecycle
- Automating the ML process
- Quiz
- Reading list
- Vertex AI and MLOps on Vertex AI
- What is vertex ai and why does a unified platform matter?
- Introduction to mlops on vertex ai
- How does vertex ai with the mlops workflow, part 1?
- How does vertex ai with the mlops workflow, part 2?
- Reading list
- Quiz
- Lab introduction Vertex AI: Qwik Start
- Training and Deploying a TensorFlow Model in Vertex AI
- Summary
- Summary
- All Readings
- Your Next Steps
- Course Badge
Google via Google Cloud Skills Boost
8 hours
Certificate Available
English
On-Demand
Beginner
Instructor
cloudskillsboost.google
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