Teaching Module Hourly volume ECTS
Scientific Computing Project Management (SCPM) UE1
– Software engineering for scientific computing (20h)
– Development environments (8h)
– Oriented-object programming (20h)
48 H6
Methods for Scientific computing (SC) UE2
– Approximation, interpolation and integration of PDEs (16h)
– Linear algebra for data science and scientific computing (16h)
– Algorithm complexity and scalability (16h)
48 H 6
High performance architecture and programming (HPC) UE3
– Technologies, hardware (16h)
– Parallel programming techniques on the CPU (16h)
– Parallel programming techniques on the GPU (16h)
48 H 6
Machine Learning algorithms (ML) UE4
– Statistics and probabilities (24h)
– Numerical algorithms for machine learning (24h)
48 H 6
High Performance Algorithms and Deep Learning (HPDA) UE5
–   Deep Learning algorithms and architectures (16h)
–   Data processing platforms (Hadoop, Spark) (16h)
–   Massive data visualization techniques and tools (16h)
48 H 6
Numerical modelling and simulation (NMS) UE6
– Discrete systems (12h)
– Continuous systems (12h)
– Optimization and inverse problems (12h)
– Stochastic and statistical methods (12h)
– Signal and image processing (12h)
24 H 3
Digital Society (NS) UE7
– HPC society (6h)
– Digital and intellectual property (6h)
– Data ethics (6h)
– Virtualization and security (6h)
24 H 3
Projects and case study (CSP) UE8 48 H 6
Conferences 20 H3