Data is basically the gold of our times. And data scientists are, well, gold diggers facing vast amounts of debris. Once they strike gold, data miners classify and analyse relevant information. In company contexts, data collection and preparation serve as the basis for corporate decision making. What is more, industrial data science contributes substantially to technological progress. The development of autonomous vehicles is a case in point: during the design process, the software of self-driving cars needs to be fed with data in order to make sure the vehicle moves safely through traffic.
Requirements and interests: what we are looking for
You feel like industrial data science sounds a bit too nerdy because it makes you think about “The Matrix”? Well, yes and no… Data science has obviously a lot to do with numbers, algorithms, computers and the proverbial attempt to find a needle in a haystack. Above all, however, data scientists are curious beings! They are in charge of fundamental decisions every company has to take. If you are conscientious, interested in technology and usually stay on top of things, you bring along key requirements for your future as a data scientist.
During your studies: what to look forward to
The particularity of the Industrial Data Science programme at Montanuniversität is the strong link between technical competencies and the ability to apply analytic methods. For this you need elementary insights that are covered by a 4-semester foundation course. You then specialise in high-tech areas such as sensor technology, cloud services, simulation, artificial intelligence and machine learning. Basic skills in business management are also an integrated part of your studies. In addition, you learn programming and how to develop and refine algorithms. A project-focused assignment with hands-on application will allow you to prove your skills and expertise straightaway.
Following your studies: what to expect
As a Montanuniversität data scientist you support decision makers by processing and analysing big data. You develop new and sustainable business plans with digital tools and refine technical processes through data-based treatments. The development of data mining and machine learning projects is also part of your remit. In the logistics sector you use data science to improve operating procedures and increase the quality and eco-efficiency of transport services. Technology companies require your expertise for the development of artificial intelligence; and the energy sector needs your support with intelligent energy networks.