Effective MLOps - Model Development
In this course, participants learn about principled ML workflows for model development and experience working with W&B tools. In order to become certified, participants are required to complete a project showing their hands-on experience with the demonstrated MLOps tools and techniques.
- Lesson 1 - Building an End-To-End Prototype (1.5 hrs)
- Lesson 2 - Hyperparameter Optimization and Collaborative Model Training (1. 5hrs)
- Lesson 3 - Model Evaluation (1.5 hrs)
Course graduate have learned the following skills:
- Accelerate and scale your model development via principled ML workflows
- Never lose track of machine learning work with experiment management
- Improve productivity with automation via hyperparameter sweeps
- Establish best practices for collaboration
- Ensure reproducibility and enterprise-level governance through data and model lineage tracking
Skills / Knowledge
- MLOps
- Weights & Biases
- ML Model Development
- Experiment Tracking
- Exploratory Data Analysis
- Model and Dataset Version Management
- Hyperparameter Optimization
- Model Evaluation
- Collaborative Model Training