AI Workshop (Virtual): Full-Stack Machine Learning with Metaflow

** RSVP: Register here to receive joining link before the deadline.
There are also two other sessions, you need to register each one:

• May 29th: AI Seminar (Virtual): Packaging Code for ML and GenAI
• May 30th: AI Workshop (Virtual): LLMs, RAG, and Fine-Tuning

Description:
This workshop is for data scientists and machine learning engineers who want to learn how to move machine learning projects from prototypes and experiments to production as a repeatable process. If you want to build production-grade, SLA-satisfying software systems in Python code, including core MLOps building blocks (such as versioning, experiment tracking, workflows, and so on), then this course is for you.

​This workshop will teach you all the ingredients of full-stack machine learning and the infrastructure you’ll need to use to deploy your ML and AI models to production. It will involve continuous, hands-on coding using our Metaflow sandbox, a browser-based VSCode environment with the ML infrastructure to power Metaflow provisioned for you at the click of a button.

​You’ll learn how to:

• - ​​Orchestrate machine learning workflows;
• - ​​​Use versioning, model reporting, and notebooks to inspect your workflows and models;
• - ​​​Leverage cloud compute resources to scale entire workflows and single steps;
• - ​​Deploy workflows and models to production systems and;
• - ​Configure A/B tests to establish iterative AI development cycles;
• - And much more.

​Warnings:
This course is not a typical data science workshop in the sense that:

• - This is an engineering-focused course, not an ML course. You will get to build actual functional systems, not learn about how to train models or run cross-validation. That said, the course is intended to be accessible to non-engineers: we want to make sure that all (data) scientists can build real-world DS, ML, and AI software systems;
• ​- Outerbounds provides managed infrastructure for the course, including data storage in S3, Kubernetes as a computing platform, workflow scheduling and event-triggering with Argo, and more - all accessed through Python files and notebooks in a familiar IDE.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations
• Join Slack/Discord (link is at the bottom of the page)

Speakers:
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: https://forms.gle/JkMt91CZRtoJBSFUA

Sponsors:
We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 350K+ AI developers worldwide.