The MSc Data Science programme offers in-depth training at the forefront of machine learning ... Bayesian Machine Learning, Distributed Computing for Big Data, Graph Data Analytics and Representation ...
The Master of Science in Big Data develops data architects who apply a deep knowledge of computer science to create new tools that find value in the vast amounts of information generated today.
Advances in computing and data science now make it possible to process and analyse big data in real time. New insights gleaned from such data mining can complement official statistics and survey ...
Omics research is an emerging field in precision medicine using big data science. The integration of omics data means that thousands of genes, proteins, RNAs, and metabolites can be studied ...
You must complete 21 credits of core coursework in statistics, computer science, and general core concepts as well as 9 credits of elective coursework. You will also participate in practical, hands-on ...
Discover how data science can help us solve pressing social problems. Learn practical programming and social scientific skills to build your future career. The rapid rise of AI and big data are ...
which focuses on real-world business applications for Big Data. Science is fascinating but solving business challenges with Big Data pays the bills, big time. Finishing this program means you will: ...
Gain advanced skills in both economics and data science that many employers are looking for. Evidence hands-on practical experience and build industry connections. Navigate state-of-the-art software ...
Identify big data or large, distributed systems. Know when and when not to use big data. Practice software engineering fundamentals. Create an application that uses rest collaboration, event ...
Risk Analysis, This collection explores the relevance of global trade law for data, big data and cross-border data flows. Contributing authors from different disciplines including law, economics and ...
Spatial Data Science covers the use of Esri’s software to support new spatial data science methods to extract additional insights from various sources of geospatial data. Through six chapters, the ...