About this Event
Data Science is a broad and diverse field comprised of a few families of methodologies: Business Intelligence, Unsupervised Learning, Supervised Learning, Reinforcement Learning, Optimization, as well as Systems Modelling & Simulation. These families are distinguished by their purposes, and the kinds of data that is required to use them.
This talk will introduce data science through an overview of its methods and where they may be applied. This talk is crafted to be accessible to the non-technical, but to also be of interest to the technologist. Hopefully, even a practicing data scientist may find something of interest.
We will begin by discussing a past data science project to give those interested in data science an idea of what a project might entail. Then, we will talk about the various families of methods and how they might be used. We will conclude by touching on how one can get started with data science.
About the Speaker
This talk will be conducted by our Head of Data Science, Jeremy.
Jeremy holds a PhD in Decision Sciences at the National University of Singapore and a Master's Degree at the Massachusetts Institute of Technology in Computation for Design and Optimization, where he did a thesis on randomised methods for convex optimization.
Jeremy later earned a PhD in Decision Sciences at the National University of Singapore in 2017, with a thesis on "Social Networks and the Choices People Make" (discrete choice on social networks). During his PhD days, he also worked on recommendation systems and a start-up building solutions for compliance in pharmaceutical manufacturing.
This event is sponsored by UpCode Academy.
UpCode Academy is a coding school based in Singapore. We impart skills like python programming, web development, data science and AI, just to name a few. We are committed to increasing the employability of our students in the tech field, thus our courses are taught by working professionals to ensure that the skills taught are of industry standards.