The mantra of this course is that the best way to learn is by doing, and we will be doing stuff together
throughout.
There will be eight commercial projects which will be applying what you're learning to real business
problems, and they'll be exercises for you to do the same thing.
And I'm hoping that you'll be able to set up GitHub and be able to make your own versions and push them
and send me a PR, a pull request, and I'll be able to merge in your code so that other people can
see your solutions too.
But you'll be able to add this to your GitHub and be able to show yourself that you are building projects
to solve real world commercial problems.
One of our projects I mentioned is going to be a chatbot assistant.
We're going to build one for an airline.
It's going to be able to do things like use tools to look up the price of tickets.
It's going to make audio and it's going to show pictures like this beautiful pop art version of London
showing here on the right as you interact with the chatbot assistant.
We're also going to be building rag pipelines, putting vectors of information in a vector data store
that you'll have running, and we'll be able to look at things like visualizations of the vectors,
mess around with them in 3D space, look into them to understand how different kinds of information
get placed in different locations in vector space, and why that is fundamental to Rag retrieval, augmented
generation.
And then, as I say, the the moment, the big moment in the project will be in week eight, when we
will build an Agentic AI solution that will bring together everything that you've learned about through
the eight weeks for something which will solve a business problem.
And I'll be able to give you some examples of how you can then apply that to solving other business
problems that you might face in the future, or that you might have today.
And you'll be able to watch as agents collaborate, you'll see the memory of the agents and see what's
going on in our agent world.
A lot to look forward to.