Starting in the academic year 2020-2021, Hasselt University will provide a comprehensive Data Science track within the Master of Statistics and Data Science. A distance-learning option will become available in 2021-2022.
More information about the full program is available at the Master of Statistics and Data Science website.
With the advent of the big data era, several global challenges that were outside of reach can now start to be addressed. In the field of medicine, wearable devices and real-time sensors generate huge amounts of data that can shed light on triggers for disease episodes. Omics and genome sequencing can aid in managing and preventing diseases, especially if they are combined with other data sources as, for example, information from social networks. Integrated analysis of weather data, credit card transactions and air pollution data sheds light on how people change their behaviour due to air pollution. Graph analysis of social network data makes it possible to identify fake accounts and fake news - a growing problem in the current political climate. The list goes on... A data scientist is someone who, apart from technical skills to tackle these issues, has a desire to dig deeper and go beneath the surface of a problem.
The Data Science specialization of the Master of Statistics and Data Science provides a comprehensive education in this field, covering the whole data science cycle from data gathering, cleaning and management, to analysis and visualisation, and finally dissemination. Apart from a very decent knowledge of statistical principles. the topics in the master therefore include (but are not limited to) data and software carpentry, programming in python and R, statistics, algorithms, machine learning (including deep learning), natural language processing and data visualisation. In addition to regular courses, students can integrate their knowledge and skills in several data science projects and a hack week.
Statisticians/data scientists needs to be able to communicate with researchers of various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.
Topics that will be covered include (but are not limited to):
- software carpentry and programming in python and R
- data carpentry, including data management and processing (SQL, NoSQL, ...)
- visual analytics
- machine learning
Data science is booming and data scientists and statisticians are in great demand. Both companies (in fields ranging from pharmaceuticals to manufacturing and banking) and the public sector are struggling to find good candidates with a solid background in data science. This shortage is a clear constraint in these sectors. Job descriptions range from covering the full data science cycle in a research setting, to specific analyses to maximise the environmental, societal or financial impact in a company. In addition, data scientists are often employed to streamline data wrangling and analysis pipelines. With the growing availability of public datasets, an exciting new opportunity also lies in data journalism where you really cover everything from defining a question, searching for data, cleaning and analysing, and dissemination.