👩‍⚕️ Basic MLOps Every Data Scientist MUST Know - Part 1

Master MLOps fundamentals in this 2-part session. Learn model lifecycle best practices like versioning, monitoring and explainability. Then, explore deployment, optimization and governance techniques to keep models performing over time in complex environments. Walk away with practical skills to successfully manage machine learning applications from development through production.

What Will Be Covered

In this session, you will,

• Get an overview of MLOps.
• Get an understanding of why is it crucial for deploying and maintaining machine learning models in production.
• Get an overview of data versioning and management (importance, tools and best practices).
• Get an overview of model lifecycle management (model development cycle, versioning models, model registry).
• Get an understanding of model monitoring and observability (metrics, logging model performance, alerts).
• Get an overview of some of the key metrics to monitor (accuracy, drift, latency, others).
• Be able to explain why continuous monitoring is important.

Upcoming Sessions

Please note:

• All times above are expressed in SGT. Click on the 🌏 icon next to sessions of interest to get your location’s corresponding date and time.
• For reference, 10 PM SGT is 7:30 PM (Bangalore), 9 PM (Jakarta), 7 PM (Lahore)

Other Dates & Times

👋 I am interested but don’t see a date or time that works for me.

You can indicate your preferred date & time when you register.

What’s Next?

What’s next after attending this session?

This session covers content that is part of the following tracks:

• Applications Of Generative AI
• ML Engineering
• Semantic Search

Check out the complete list of upcoming sessions.

Alternatively, if you are a hands-on creator, check out the upcoming Hands-On Learning Sessions.