Hands-on MLOps Workshop: From Training to Deployment
Join us for an exclusive, industry-led hands-on MLOps workshop designed to take you through the entire machine learning lifecycle — from model training to real-world deployment!
In this interactive session, you will:
✅ Train a compact CNN model on the CIFAR-10 dataset
✅ Track experiments and performance metrics using MLflow
✅ Deploy the trained model through a FastAPI web API
✅ Containerize your application with Docker
✅ Automate testing and builds via GitHub Actions (CI/CD)
✅ Run your complete setup locally using Docker Compose
💡 Why attend?
Learn modern MLOps best practices from two industry experts actively applying these tools in the field.
Gain hands-on experience integrating key tools used in real-world ML pipelines.
Perfect for students who are interested in Deep Learning, Data Mining, or any AI-related fields and want to bridge the gap between model development and production deployment.
🎙️ Guest Speakers:
Dr. Megha Kalia — AI Applied Scientist, Zepp Health
Navid Mahdian — Robotics Software Engineer, RoboTools Canada
Alejandro Aguirre — PhD Candidate in Bioinformatics, University of British Columbia (UBC)
📢 Note: Detailed instructions about the required software installations will be shared with all registered participants prior to the workshop.
💻 Bring your laptop — this is a fully hands-on session!
☕ Light refreshments will be provided.
Seats are limited — register now to secure your spot!
Organized in Partnership with Vancouver Data Science Reading Group, Career Development and Experiential Learning and College of Engineering.