120 credits in science/engineering including 50 credits in computer science and mathematics, of which at least 20 credits in computer science and 20 credits in mathematics. Computer science is to include at least 10 credits programming and participation in Database Design I. Mathematics is to include linear algebra and probability and statistics. Proficiency in English equivalent to the Swedish upper secondary course English 6.
This course gives an introduction to the challenges involved in the analysis of datasets that are so large that it is no longer possible to handle them using traditional databases and traditional software. Such datasets can for example be generated from experiments and simulations in science or the social sciences. A common problem in large-scale machine learning is transforming and computing features from massive datasets as preprocessing to model training. The course covers how modern systems are designed to scale well with respect or performance, robustness and economy. It also gives a hands-on introduction to commonly used frameworks. The focus is on batch analysis and the practical use of cloud computing resources.
