Master Specialisation Data Science - General introduction
Data plays a role in almost every scientific discipline, business industry or social organisation. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour with huge telescopes and the police employ seismology-like data models that predict where crimes will occur. And of course, businesses like Google and Amazon are shifting user preference data to fulfil desires we don’t even know we have. Many companies complain about the difficulty to find skilled data scientists and predict this to be even harder in the future. There is therefore an urgent need for data scientists in whole array of fields.
The Master specialisation Data Science trains you to become a curious, creative, and competent data scientist. As an academic, we do not just expect you to understand and make use of the appropriate tools, but also to program and develop your own. You will follow core courses in machine learning, information retrieval, and probabilistic modeling, and can then delve deeper into different application areas such as natural language processing, medical pattern recognition, neuroimaging, business rules and/or bioinformatics. You’ll learn how to turn data into knowledge with the help of computers and how to translate that knowledge into solutions.
A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data, to come up with a creative and useful solution, to find or program the right tool to turn the data into knowledge, and to communicate the obtained findings to others. By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.
Although this Master specialisation is an excellent stepping-stone for students with ambitions in research, most of our graduates work as data consultants and data analysts for commercial companies and governmental organisations.