Courses

The program in Data Science and Scientific Computing is organized in two curricula: 

Each curriculum is further organized in several study plans, each corresponding to a specific application area, proposing a choice of specialization courses. 

Check out the Study Plan page for more information.

 

Select one or more paths

Numerical Methods in Quantum Mechanics

Objective: providing an introduction to numerical methods and techniques for the numerical solution of quantum mechanical problems, especially in atomic physics and condensed matter, with a practical approach.

Oceanography

Objective: providing a basic knowledge of the physical oceanography and how to integrate theoretical knowledge with experimental measurements.

Open Data Management and the Cloud

Objective: providing students with practical information on how to design data models and data structures, to manage metadata to optimize access and research, and to become familiar with interoperability standards. The course will focus on the concept of open data, with efficiency for big data projects, and the concept of cloud as an infrastructure for data management and their processes.

Optimal and Robust Control

Objective: providing the foundations of the modern approach to the control of dynamical systems, with particular reference to the treatment of uncertainty, structured and unstructured. Provide the main tools and methods for the analysis and synthesis of multiple-input-multiple-output control systems.

Optimisation and Design

Objective: providing expertise on optimization techniques, with applications to industrial design.

Optimisation Models

Objective: providing students with the methodological, theoretical and practical tools to formulate linear programming models and combinatorial optimization problems and to solve them, even for high dimensionality problems, using appropriate optimization software.

Optimization Models

Objective: providing students with the methodological, theoretical and practical tools to formulate linear programming models and combinatorial optimization problems and to solve them, even for high dimensionality problems, using appropriate optimization software.

Physics of Atmosphere

Objective: provide knowledge of the fundamental properties of the dynamics and thermodynamics of the atmosphere, and the formulation and implementation of some simple analytical models of atmospheric dynamical systems.

Simulation of Multibody Systems

Objective: providing the ability to understand the functioning and the internal structure of a molecular dynamics program. Being able to write code for molecular dynamics simulations and to analyze the output.

Social Network Analysis

Objective: presenting statistical analysis techniques for social networks and other social and economic networks.

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