Data Science Forum



Would you like to explore rapidly advancing breakthrough technology and cutting-edge science? Are you interested in knowing how technology and entrepreneurship can have a positive impact on global challenges?

The newly launched Data Science Forum is dedicated to the dissemination of methodological insight and applications in the areas of computational statistics and data analysis. We also take a keen interest in every major AI area, including NLP, computer vision, and machine learning. The aim of the forum is two-fold. First, to invite brilliant technology and business leaders to Birkbeck in order to learn about how the latest technologies can lead to great business results. Second, together with our knowledge partners, we are launching a Data Science Academy in order to facilitate access to the latest data science techniques. Whether you are looking to get yourself well ahead of the curve for the job market, develop an expert understanding of IT workflows, or simply learn about the latest technology trends, we have you covered.

Our mission is simple: to provide a bridge between research and industry to apply emerging technology, science & entrepreneurship to share, collaborate, and inspire.

The forum will kick off with a series of events, aimed at all Birkbeck students with an interest in data science. All events are free to attend.


Coming soon:


Industry insight session

Title: Applications of Data Science and Machine Learning in Finance
Speaker: The speaker is a senior industry professional and Head of Algorithmic Trading at a top European bank.
Areas covered: Artificial Intelligence & Data Science in Finance: the Past, the Future, and Job Market options.

Practical learning session

Title: Introduction to machine learning algorithm development
Speaker: The instructor is a senior industry professional from a partner institution.
Areas covered: This 3-hour course introduces topics in machine learning algorithm development in Java. Using the Clusterer class available from the “Apache Common Math” library, the following algorithms are explained: KMeans++, Fuzzy-KMeans, Density-based spatial clustering of applications with noise (DBSCAN) and Multi-KMeans++.


Register to learn more.



powered by Typeform


The Data Science Forum is led by students and alumni and is not for profit. Any opinions and views expressed are solely those of the Data Science Forum and do not necessarily represent the views of Birkbeck, University of London.