- Level Expert
- Duration 13 hours
- Course by Duke University
-
Offered by
About
This course covers two of the most popular open source platforms for MLOps (Machine Learning Operations): MLflow and Hugging Face. We’ll go through the foundations on what it takes to get started in these platforms with basic model and dataset operations. You will start with MLflow using projects and models with its powerful tracking system and you will learn how to interact with these registered models from MLflow with full lifecycle examples. Then, you will explore Hugging Face repositories so that you can store datasets, models, and create live interactive demos. By the end of the course, you will be able to apply MLOps concepts like fine-tuning and deploying containerized models to the Cloud. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their programming skills.Modules
About the Course
2
Discussions
- Meet and Greet (optional)
- Let Us Know if Something’s Not Working
1
Videos
- Meet your Course Instructor: Alfredo Deza
3
Readings
- Meet your Supporting Instructor: Noah Gift
- Course Structure and Discussion Etiquette
- Getting Started and Best Practices
Introduction to MLflow
1
Assignment
- Introduction to MLFlow
4
Videos
- Overview of MLflow
- Installing and Using MLflow
- Introduction to the Tracking UI
- Parameters, Version, Artifacts and Metrics
3
Readings
- Key Terms
- What is MLFlow?
- Lesson Reflection
MLflow Projects
1
Assignment
- MLflow Projects
4
Videos
- Working with MLflow Projects
- Create an MLflow Project
- Run Project from Remote Git Repositories
- Connecting MLflow to Databricks
3
Readings
- Key Terms
- MLflow Projects
- Lesson Reflection
MLflow Models
1
Assignment
- MLflow
1
Labs
- MLflow Projects
4
Videos
- Components of an MLflow Package
- Using a Registry with an MLflow Model
- Referencing Artifacts with the API
- Saving and Serving MLflow Models
3
Readings
- Key Terms
- MLflow Models
- Lesson Reflection
Introduction to Hugging Face
5
Videos
- What is Hugging Face?
- Overview of the Hugging Face Hub
- Introduction to the Hugging Face Hub
- Using Hugging Face Repositories
- Using Hugging Face Spaces
3
Readings
- Key Terms
- Hugging Face Hub
- Lesson Reflection
Introduction to Applied Hugging Face
3
Videos
- Introduction to Applied Hugging Face
- Using GPU Enabled Codespaces
- Using the Hugging Face CLI
3
Readings
- Key Terms
- Hugging Face CLI
- Lesson Reflection
Using Hugging Face
1
Assignment
- Hugging Face Fundamentals
1
Labs
- Introduction to Hugging Face
6
Videos
- Using the Model Hub
- Downloading Models
- Working with Models
- Adding Datasets
- Using Datasets
- Working with Datasets
3
Readings
- Key Terms
- Datasets
- Lesson Reflection
Packaging Hugging Face
1
Assignment
- Quiz-Packaging Hugging Face
4
Videos
- Hugging Face and FastAPI
- Containerizing Hugging Face
- Running FastAPI with Hugging Face
- CI/CD Packaging with GitHub Actions
3
Readings
- Key Terms
- FastAPI
- Lesson Reflection
Hugging Face and Azure ML Studio
1
Assignment
- Hugging Face and Azure
5
Videos
- Hugging Face and Azure ML Studio
- Registering a Hugging Face Dataset on Azure
- Registering a Hugging Face Model on Azure
- Inspecting a Hugging Face Dataset on Azure
- Azure ML Python SDK
3
Readings
- Key Terms
- Azure ML Python SDK
- Lesson Reflection
Hugging Face Automation
1
Assignment
- Deploying Hugging Face
1
Labs
- Packaging Hugging Face
4
Videos
- Using GitHub Actions for Model Deployments
- Using Azure Container Registry
- Automating Packaging with Azure Container Registry
- Automating Packaging with Docker Hub
3
Readings
- Key Terms
- Docker Overview
- Lesson Reflection
Hugging Face with Azure Containers
1
Assignment
- Quiz-Hugging Face with Azure Containers
4
Videos
- Create an Azure Container Application
- Configure an Azure Container Application
- Deploy Hugging Face to Azure
- Troubleshooting Container Deployment
2
Readings
- Key Terms
- Lesson Reflection
Fine-Tuning and ONNX Exporting
1
Assignment
- Quiz: Fine-Tuning and ONNX Exporting
1
Labs
- Hugging Face and ONNX
4
Videos
- Introduction to Fine-Tuning Theory
- Performing Fine-Tuning
- Introduction to ONNX and Hugging Face
- Exporting Hugging Face Models to ONNX
2
Readings
- Key Terms
- Lesson Reflection
Beyond Hugging Face Spaces
1
Assignment
- Applied Hugging Face
4
Labs
- Deploying Hugging Face
- Final Jupyter TensorFlow Sandbox
- VSCode Final Sandbox
- Linux Desktop Final Desktop
9
Videos
- Introduction to Hugging Face Spaces
- Hugging Face Spaces Walkthrough
- Deploying Hugging Face Spaces
- Profit Sharing Concepts
- Tragedy of the GenAI commons
- Game Theory of GenAI
- Perfect Competition
- Negative Externalities
- Regulatory Entrepreneurship
6
Readings
- Key Terms
- Regulatory Entrepreneurship
- Ethical Sourcing of Datasets
- Glaze
- Lesson Reflection
- Next Steps
Auto Summary
Explore the world of MLOps with the "MLOps Tools: MLflow and Hugging Face" course on Coursera. This expert-level course, designed for both beginners and seasoned professionals, delves into the foundational aspects of MLflow and Hugging Face. Learn to manage datasets, fine-tune models, and deploy them to the Cloud with practical, hands-on examples. The course spans 780 minutes and offers a Starter subscription, making it an ideal choice for those looking to enhance their skills in Data Science and AI. Join now and elevate your MLOps expertise!

Noah Gift

Alfredo Deza