Accelerate your AI/ML projects with an MLOps workshop
Build your tailored MLOps architecture in just 5 days. Our workshop will help you design AI infrastructure for any use case – from the data center to the edge. Accelerate and scale your AI/ML initiatives, optimize resource usage and elevate your in-house expertise.
Why join an MLOps workshop?
Define your MLOps architecture
We will work with you to build high-level and low-level architecture based on your existing infrastructure for your AI/ML projects, using only open source tooling.
You can expect:
- An end-to-end proposal, covering everything from the operating system to the data science and ML platform
- Cloud-agnostic design
- Cost-efficient solution
- Scalable and secure architecture that runs from AI workstations to data centers to edge devices, depending on your AI/ML maturity
Learn from experts in the industry
Spend 5 days on site with Canonical experts who will help upskill your team and solve the most pressing problems related to MLOps and AI/ML.
- Get guided, hands-on experience with the latest open-source ML tooling, adjusted to your use case and needs
- Live Q&A session with AI and MLOps experts to help you accelerate time-to-market and unblock your projects
- Access a library of written content to further upskill after the workshop
Make the best use of existing infrastructure
Optimize your existing infrastructure to maximize efficiency and performance for your AI/ML workloads. Learn about:
- Data collection improvement opportunities
- GPU optimization techniques and strategies
- Model packaging and distribution best practices
MLOps workshop structure
Open source migrations
Build a migration plan to move your infrastructure to open source solutions to enable a long term strategy.
MLOps architecture design
Discover infrastructure options, MLOps processes and tools to make informed decisions about your stack.
Resource optimization
Stop underutilizing your compute power and learn how to optimize your resources across all layers of the stack.
Edge AI
Develop Edge AI architecture to efficiently run and maintain your models on a variety of devices.
You can also customize these workshops based on your needs, or even build your own bespoke agenda by selecting the topics that are most valuable for your organization.
Meet our experts
Your MLOps workshop is delivered by Canonical's MLOps field engineering team, a team of experts trained to architect, design and deploy AI infrastructure at all scales, across industries.
From GenAI use cases to AI sovereign clouds, the team has experience in building solutions in partnership with our customers.
Learn more
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Explore how Canonical delivered significant cost-savings in moving away from licensed providers and proprietary solutions.
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Case study: Real-time space tracking with AI supercomputing
Read how the University of Tasmania migrated from a legacy platform to Canonical MLOps and reduced their operational costs.
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Managed AI infrastructure
Learn more about the key considerations, opportunities and common pitfalls of managing AI infrastructure.