As the need for data to fuel AI applications grows, tools to organise data are proliferating As discussed in a previous post, the data engineering team (DE) at AI Singapore was formed to architect and deploy a data platform for our organisation. A more robust and consistent approach to data management has been expressed as
Recently, I came across this old article from Stitch Fix and it set me thinking about the kind of work we do here in AI Singapore and what it takes to be an AI Apprentice and progress on to become an AI Engineer. Continuing from my previous article, I think it is time to showcase
The newly formed Data Engineering team at AI Singapore has plans to refine data management practices in tandem with the growth in number of projects Toward a Common Data Platform The AI Innovation team at AI Singapore has evolved from a few staff to a strong collection of engineering teams in the last two years.
At AI Singapore, we are constantly running several 100 Experiments (100E) projects. To ensure smooth and successful delivery, it is essential to have some form of a structured methodology that help guide the team. For this, we adopt well known principles of Lean and Agile development where common frameworks used include Scrum, Kanban and others.