Master of Science in Computational Science (MCS)
Courses 2023-2024
Fall semester
Lecture
Elective
- Advanced Topics in Machine Learning, Alippi C., Carman M., Cini A., Manenti A., Marisca I.
- Algorithms & Complexity, Arseneva E., Papadopoulou E., Oliver Burwitz N., Wang Z.
- Analysis of Social Networks, Amati V., Lomi A.
- Artificial Intelligence (MSc), Gambardella L. M., Bedi N. S., Encz K. I.
- Bioinformatics, Limongelli V.
- Computational Biology and Drug Design, Limongelli V.
- Databases, Crestani F., El Moussa N.
- Deep Learning Lab, Vercesi E., Dei Rossi A., Marzi T., Palomba M.
- Distributed Algorithms, Pedone F., de Lima Batista E. R., Milosevic N.
- Distributed Systems, Eugster P. T., Bedi N. S., Peykani Sani P., Rovelli D.
- Introduction to Ordinary Differential Equations, Krause R., Rosilho de Souza G., Vitali F.
- Machine Learning (MSc), Wand M., Ashley D. R., Gopalakrishnan A., Herrmann V., Hou Q.
- Numerical Algorithms, Hormann K., Fuda C.
- Scattered Data Approximation, Multerer M., Quizi J.
- Software Tools for Computational Biology, Raniolo S.
Lecture and Laboratory
Project
Spring semester
Lecture
Elective
- Advanced Computer Architectures, Pozzi L.
- Advanced Networking, Carzaniga A.
- Computational Fabrication, Didyk P. K.
- Computer Vision & Pattern Recognition, Hormann K.
- Data Analytics, Crestani F.
- Discretization Methods, Pivkin I.
- Effective High-Performance Computing & Data Analytics, Schenk O.
- Geometric Algorithms, Arseneva E., Papadopoulou E.
- Graph Deep Learning, Alippi C.
- Graphical Models and Network Science, Wit E. C.
- Information & Physics, Wolf S.
- Information Security, Langheinrich M.
- Introduction to Bayesian Computing, Mira A.
- Introduction to Partial Differential Equations, Baroli D.
- Particle Methods, Pivkin I.
- Quantum Computing, Wolf S.
- Scientific Learning, Krause R.
- Stochastic Methods, Richter Mendoza F. J.
- Text Analysis and Spatial Data for Economists, D'Ambros M., Parchet R., Albertini M.
