What Will You Learn?
Know why and when deploying MLOps can help your (tiny) product or business
Key MLOps platform features that you can deploy for your data science project
How to automate a MLOps life cycle
Real-world examples and case studies of MLOps Platforms targeting tiny devices
About This Course
Provider: Edx
Format: Online
Duration: 28 hours to complete [Approx]
Target Audience: Advanced
Learning Objectives: After completing this free course, you will explore best practices to deploy, monitor, and maintain (tiny) Machine Learning models in production at scale.
Course Prerequisites: NA
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Harvard University
Key Topics: Automation, Data Science, Mathematical Optimization, Smartphone Operation, Infrastructure, Machine Learning, Benchmarking, Product Lifecycle, Operations
Topic Covered:
- - Welcome
- - ML Development
- - Training Operationalization
- - Continuous Training
- - Model Conversion
- - Model Deployment
- - Prediction Serving
- - Continuous Monitoring
- - Data & Model Management
- - Responsible AI: Transparency & Sustainability
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