Mathematics

Mathematics is the study of logical connections between abstract concepts such as numbers, sets, functions and geometric objects. Mathematical statements are derived by means of logical reasoning and when a mathematical statement is proved, it remains valid for the future, regardless of what reality looks like. In this way, mathematics achieves a general validity that is not only fascinating but also makes mathematics an excellent tool for understanding many different phenomena. For example, one single mathematical model can explain both fish shoal and democratic development.

People who have good knowledge of mathematics are good at detecting patterns and solving very advanced problems from many different angles. This capability is a valuable asset in many industries where a large amount of information needs to be processed and interpreted.

Mathematics is also a living research topic that is constantly evolving. The mathematical research in Uppsala underwent internationalisation in the 1990s and has since multiplied, both in terms of the number of active researchers and research areas.

Courses

Bachelor's level, basic courses

Mathematics I, 30 credits

Bachelor's level, continuing courses

Algebra II, 5 credits Combinatorics, 5 credits Inference Theory I, 5 credits Inference Theory II, 5 credits Introduction to Scientific Computing, 5 credits Linear Algebra II, 5 credits Logic and Proof Techniques I, 5 credits Mathematical Methods of Physics, 5 credits Multivariate Methods, 10 credits Ordinary Differential Equations I, 5 credits Probability Theory I, 5 credits Probability Theory II, 5 credits Regression Analysis, 5 credits Several Variable Calculus, 10 credits

Master's level courses

Analysis of Categorical Data, 5 credits Analysis of Time Series, 10 credits Bayesian Statistics, 10 credits Computer-Intensive Statistics and Applications, 10 credits Computer-Intensive Statistics and Data Mining DS, 7.5 credits Dynamical System and Chaos, 5 credits Financial Derivatives, 7.5 credits Foundations of Data Science, 10 credits Generalised Linear Models, 5 credits Introduction to Data Science, 10 credits Markov Processes, 10 credits Mathematical Modelling of Football, 5 credits Mathematical Topics in Data Science, 7.5 credits Modelling Complex Systems, 10 credits Physics and Finance, 5 credits Scientific Computing, Bridging Course, 5 credits Statistical Machine Learning, 5 credits Theoretical Foundations for Data Science, 7.5 credits Topics in Data Science, 5 credits

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