MACHINE LEARNING · 4 WEEKS · 105 LESSONS
MLOps Tools: MLflow and Hugging Face
Learn to effectively manage machine learning workflows using MLflow for experiment tracking and Hugging Face for model deployment. Master essential MLOps tools through hands-on experience with industry-standard practices.
Master essential MLOps tools with this comprehensive course covering MLflow and Hugging Face. Learn to manage machine learning lifecycles, track experiments, deploy models, and leverage the Hugging Face ecosystem for efficient AI development. Through hands-on exercises, discover how to streamline ML workflows, implement version control for models, automate deployments, and integrate with cloud services like Azure for production-ready AI applications.
01 — What learners say
Real feedback from real learners.
“The Rust Fundamentals course was fantastic for formalizing my base Rust knowledge. It was well-paced for both beginner and experienced developers.”
“The course was incredibly informative and well-structured. I gained practical skills that immediately applied in my work, making it a highly valuable learning experience.”
“The course on AI Fundamentals is not only engaging but also practical. Having worked with AWS before, the way it explained Azure cncepts made switching seamless and easy to grasp.”
“I can say that it's a great series of courses for those who are looking to practical MLOps knowledge.”
“This course got clear videos, exercises, and questions, and there are extra resources too. When you're done, you'll have a solid foundation to dive into topics like DevOps or ML.”
02 — Why this course
What you'll walk away with.
Master essential MLOps tools with this comprehensive course covering MLflow and Hugging Face. Learn to manage machine learning lifecycles, track experiments, deploy models, and leverage the Hugging Face ecosystem for efficient AI development. Through hands-on exercises, discover how to streamline ML workflows, implement version control for models, automate deployments, and integrate with cloud services like Azure for production-ready AI applications.
Master MLflow fundamentals including experiment tracking, project management, and model registry
Deploy and manage machine learning models using Hugging Face's ecosystem and tools
Implement automated ML pipelines with Azure integration and containerization
Apply best practices for model versioning, packaging, and deployment automation
03 — Syllabus
4 weeks, 105 lessons total.
- Meet your supporting instructor NOAH gift
- Course structure and discussion Etiquette
- Getting started and best practices
- Key terms
- Overview of Mlflow
- Installing and using Mlflow
- Key terms
- What is Hugging face
- Overview of the Hugging face hub
- Introduction to the Hugging face hub
- Using Hugging face Repositories
- Using Hugging face spaces
- Key terms
- Hugging face and Fastapi
- Containerizing Hugging face
- Running Fastapi with Hugging face
- Ci CD packaging with Github actions
- Fastapi
- Key terms
- Create an Azure container application
- Configure an Azure container application
- Deploy Hugging face to Azure
- Troubleshooting container deployment
- Quiz
04 — For teams
Custom training for your company.
We're ready to deliver this and other courses to your team. We accommodate different requirements and are flexible with seat count.
- +Bulk pricing available
- +Customizable content
- +Ready to start on your schedule
05 — Individual access
Simple, straightforward pricing.
Full platform access — every current and future course — priced so cost isn't what decides whether you learn.
No commitment required. Cancel anytime.