Data Science and Engineering — Politecnico di Torino, Torino

Il piano degli esami

1° anno

• Data management and visualization — 8 CFU
• Data science and machine learning lab — 8 CFU
• Data Ethics and Data Protection — 6 CFU
• Distributed architectures for big data processing and analytics — 8 CFU
• Fundamentals of Artificial Intelligence, Machine and Deep Learning — 10 CFU
• Mathematical and statistical methods for Artificial Intelligence — 8 CFU
• Computational linear algebra for large scale problems oppure Statistical methods in data science (scegli 8 CFU): Computational linear algebra for large scale problems 8 CFU; Statistical methods in data science 8 CFU
• Decision making and optimization oppure Information Theory for Data Science oppure Numerical optimization for large scale problems (scegli 8 CFU): Decision making and optimization 8 CFU; Information Theory for Data Science 8 CFU; Numerical optimization for large scale problems 8 CFU

2° anno

• Innovation management — 6 CFU
• Thesis — 22 CFU
• Applied data science project oppure Computer-aided simulations lab oppure Geometric Learning, Time-Variant Data analysis, and Anomaly Detection oppure Network Dynamics and Learning (scegli 8 CFU): Applied data science project 8 CFU; Computer-aided simulations lab 8 CFU; Geometric Learning, Time-Variant Data analysis, and Anomaly Detection 8 CFU; Network Dynamics and Learning 8 CFU
• Deep natural language processing oppure Efficient Computing for Artificial Intelligence (scegli 8 CFU): Deep natural language processing 8 CFU; Efficient Computing for Artificial Intelligence 8 CFU
• Challenge oppure Free ECTS credits (scegli 12 CFU): Challenge 8 CFU; Free ECTS credits 12 CFU