- [Jonathan] In my day job, I work in data science,
artificial intelligence, and machine learning
for a consultancy.
So over this course, I'm going to share things
that have worked in the teams that I've been involved in.
This is a course for those who want to introduce
AI into the business, and my intended audience
are business leaders, product owners, and data scientists.
At a high level, this is what's involved.
An understanding of where the business is,
so that's using an AI assessment,
the preparation and presentation of the business case
to introduce AI into the organization,
the team that gets working on the AI project,
I'll call this the AI squad,
who then use the scrum methodology
to actually implement the AI project,
and finally, you want to deploy and monitor
the AI solution once it's in production.
I've broken the framework down into four key stages,
so there's the business understanding,
the next phase is the data collection and analysis,
you then create the AI model and evaluate it,
and finally, you deploy and monitor
the AI model in production.
So I think it's important that the four stages
have deliverables so that you're working
towards an objective at each stage.
So for the business understanding stage,
the deliverable is the business case approval.
For the data collection and analysis,
your deliverables are the business use cases.
For AI modeling and evaluation, the deliverable
is the actual AI model,
and finally for the deploying and monitoring phase,
the deliverable is an AI model
that is monitored in production
and works within accepted accuracy parameters
as defined by the business.
We'll actually develop and implement
the AI solution into production
and monitor it via the scrum methodology.