Master of Science in Computational Science (MCS)
Courses 2024-2025
Fall semester
Lecture
Elective
- Advanced Topics in Machine Learning, Alippi C., Carman M. J., Manenti A., Marisca I., Marzi T.
- Algorithms & Complexity, Papadopoulou E., Encz K. I., Wang Z.
- Analysis of Social Networks, Bianchi F., Lomi A., Richter Mendoza F. J., Malaspina A.
- Artificial Intelligence (MSc), Lanzi P., Likaj S.
- Bioinformatics, Limongelli V.
- Computational Biology and Drug Design, Limongelli V.
- Databases, Crestani F., Verdolotti E.
- Deep Learning Lab, Vercesi E., Dei Rossi A., Dominici G., Huber S.
- Distributed Algorithms, Pedone F., de Lima Batista E. R., Martignetti L.
- Distributed Systems, Chuprikov P., Mohammadpourfard A., Rovelli D.
- History of Computing, Schmutterer F.
- Introduction to Ordinary Differential Equations, Richter Mendoza F. J., Quizi J.
- Machine Learning (MSc), Wand M., Alcaide E., Andronov M., Ashley D. R., Herrmann V.
- Numerical Algorithms, Hormann K., Fuda C.
- Scattered Data Approximation, Multerer M., Avesani S.
- Software Atelier: Simulation, Data Science & Supercomputing, Schenk O.
Lecture and Laboratory
Project
Spring semester
Lecture
Elective
- Advanced Networking, Carzaniga A.
- Computational Fabrication, Didyk P. K.
- Computer Architectures and Logic Design, Pozzi L.
- Computer Vision & Pattern Recognition, Hormann K.
- Data Analytics, Crestani F.
- Data Management, Eugster P. T.
- Discretization Methods, Pivkin I.
- Geometric Algorithms, Papadopoulou E.
- Graph Deep Learning, Alippi C.
- Graphical Models and Network Science, Wit E. J.
- Information & Physics, Wolf S.
- Information Security, Langheinrich M.
- Introduction to Bayesian Learning, Mira A.
- Particle Methods, Pivkin I.
- Quantum Computing, Wolf S.
- Stochastic Methods, Richter Mendoza F. J.
- Text Analysis and Spatial Data for Economists, D'Ambros M., Parchet R., Albertini M.
Lecture and Laboratory
