edX
edXDevOps, DataOps, MLOps
125 studentsBEGINNEREnglish
Korshub's take
MLOps End-to-End: From Model to Production
Building an ML model is 10% of the work. This course tackles the other 90%: integrating DevOps, DataOps, and MLOps into a coherent pipeline from GitHub to deployment. You'll use GitHub Copilot, Gradio, Hugging Face, and containerization to move quickly.
Real projects drive learning: Optimization problems, simulations, and heuristics show you ML applied, not just theoretical.
The payoff: Holistic MLOps skills that make you valuable across data science, engineering, and operations teams.
About this course
Apply Real-World Machine Learning with DevOps, DataOps & MLOps
- Master end-to-end MLOps solutions through hands-on AI pair programming
- Leverage cutting-edge tools like GitHub Copilot, Gradio & Hugging Face
- Build containerized ML apps deployable across cloud platforms
Course Journey:
- Explore MLOps landscape and pre-trained models to solve business problems
- Apply ML/AI in practice through optimization, simulation & heuristics
- Develop integrated DevOps, DataOps & MLOps pipelines on GitHub
- Package ML solutions in containers for seamless cloud deployment
- Transition to Rust for high-performance GPU-accelerated ML tasks
Ideal for data scientists, software engineers, analysts & professionals working with machine learning. Gain holistic MLOps skills through real-world projects.
Price
$449
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