Canonical

MLOps advisory
Start your AI/ML journey now with Canonical

From retail to energy, from utilities to manufacturing, AI/ML initiatives fulfil a variety of use
cases that have different requirements and needs. While sometimes getting started is the mostdifficult part, many enterprises report challenges when it comes to project complexity. Let’s join
forces and see how we can ship your machine-learning models to production.

Canonical offers five types of MLOps advisory services that aredesigned to help you benefit from your AI/ML initiatives

Data exploration workshopKubeflow training

Get to know your data better and learn about
possible use cases based on a data sample thatyou share with us.

Learn more about our MLOps tool of choice: fromfeatures to customisation options, from deployment
to admin tasks.

MLOps workshop

Outcome-based PoC

Discover infrastructure options, MLOps
processes and tools to make informed decisions
about your stack.

Work with us to build a PoC before investing ininfrastructure for advanced use-cases. This allows
you to assess your return on investment carefully.

E2E consulting
Have an expert from our team by your side
during the entire AI/ML project and letthem drive it.

Leaders in Artificial Intelligence choose Ubuntu

Learn more about Canonical’s MLOps offering
Data exploration
workshop
Expectedoutcome

MLOps Workshop

Outcome based PoC• Data quality assessment • 5-day, on-site workshop • MLOps architecture forthe agreed use casefor up to 10 participants• MLOps architecture• MLOps knowledge and• Architecture building
proposalbest practices from abased on customer’s• Data collection
domain expert
use case
improvements proposal• Infrastructure• MLOps architecture
optimisation proposal
proposal

E2E consulting• Dedicated data solutionarchitect• Dedicated TechnicalAccount Manager, as
described here.

More information
provided below
Deliverables• Hands-on session with a • High-Level Design and
Low-Level Design of an
domain expert (2-4h)
MLOps setup• Ad-hoc question for the• Lifetime access tonext 3 business days
a library of MLOps• Written businessresources and hands-on
case definition
exercises• Exploratory data
• Q&A session
analysis (EDA) using
provided data samples• PoC covering a single
use case• PoC based on customer
data and infrastructure
or on public cloud• Milestones anddeliverables agreed
beforehand in thestatement of the work.

• Outcome presentation
and Q&A session
Best fitenterprise• Wants to assess
possibilities forusing AI/ML• Gather data, but lackknowledge on how
to set up efficient
data collection• Looking to understandstate-of-the-art MLOps
solutions based on theenterprise’s use cases• Needs assistance forhands-on exercises• Struggle with projectcomplexity• Aware of the AI/ML
opportunities• Have collected enoughdata to develop anddeploy ML models• Need an external
quality assessment foran existing solution
Out of scope

Pricing

Implementation of any
model or PoCs based on
exploration result$ 15,000

Implementation of
production-ready
MLOps pipelines$ 30,000• Looking for support
through the entire
process, from use
case exploration toproduction scaling• Are in need for experts
who can temporarily be
assigned to their teams

PoC is not committed todelivering a model metric(eg: Accuracy, F1 score)$ 3,000/ dayContact us

MLOps workshop
Day 1: Introduction to MLOps
Get started with MLOps, learning the theoreticalconcepts and how they fit within your company. During
the first day, you will get knowledge about machinelearning, different data types, roles and responsibilities
in ML projects and how to assess their maturity level.
By the end of the day, participants will have a good
grasp of various MLOps tools and platforms, comingfrom the open-source landscape. They will be able
to map them against use cases and take constraints,
dependencies and development opportunities
into account.

Day 2: MLOps architectures
During the day, your team will become familiar with
MLOps architecture, such as batch and streaming,and get to know what the deciding factors are whenchoosing one. This will allow participants to gather
knowledge about ML operations and recommended
tools to achieve your team’s goals.
By the end of the day, participants are expected tobetter understand how to obtain price-performance
optimisation, starting with the infrastructure layer.
It will include a wide presentation about Charmed
Kubeflow: from deployment to production.

Day 3: A hands-on exercise
During the third day, participants gain hands-on
experience, using an example dataset. Our MLOps
experts will guide the team through the process, so thateveryone is able to automate their own use case using
a common MLOps platform. It is a joint effort, whereparticipants analyse the dataset, train models, hostthem and learn more about packaging requirements.

By the end of the day, the audience will have anend-to-end experience using Canonical’s tooling for
MLOps, integrated with other open-source products.
It will give them a deeper understanding of the state ofdeep learning and how they can use it further.

Day 4: MLOps Becoming a pro
MLOps is more than fun coding. Learning about bestpractices ensures reliability and success in shipping
models to production. On the fourth day, our experts
will walk the participants through security and privacy
concerns, testing frameworks and model vulnerabilities.
By the end of the day, the audience will know how tosecurely approach an AI/ML project, in order to staycompliant. Debunking some myths about machinelearning is our purpose on this day.

Day 5: MLOps at your choiceThis is a summary of the learnings from the previousdays; participants use their own project data andinfrastructure. Its purpose is to show immediatebusiness value within the organisation and unblock
AI/ML initiatives.
By the end of the day, the audience will have a seed todevelop their AI/ML project of choice. Our experts will
provide further guidance on how to develop it, ensuringthat the project follows best practices and can achieve
the best possible results.

Read more about how to get started with AI and Charmed Kubeflow
Contact us to talk to an expert or direct all at(US Central) +1 737 204 0291 and or (UK) +44 203 656 5291

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