M4062 - ECTS

M4083 - ECTS

1. Train the student for regression analysis involving continuous or discrete responses (generalized linear models)
2. Implement statistical analyses in suitable software
3. Promote critical thinking in a data analysis process (data collection, modeling, interpretation of results, ...)

M4122 - ECTS Domain of the most relevant computational methods and principles underlying modern statistical  analysis and inference and application to the analysis of several types of data.

M4042 - ECTS

M4045 - ECTS

The course aims to introduce n aa rigorous the optimization theory (linear and nonlinear), variational calculus and theory of control. The fundamental concepts of these areas are addressed, as well as the most important mathematical tools for its analysis.

 

M4064 - ECTS

Students should be able to distinguish and recognise the properties of the different stochastic processes studied, such as: the Poisson process, renewal processes, Markov chains and Brownian motion. Students should also be able to use the most common processes as modelling tools. Students should also manage to simulate the different processes and use their respective properties to answer concrete problems.

M4113 - ECTS The aim of this course is to introduce the students to time series analysis methods.

M4081 - ECTS

Upon successful completion of this course, the student will:

• Know most of the classical examples of error correcting codes;
• be able of reproducing key results of the theory and give rigorous and detailed proofs of them.
• be able of constructing new codes from old ones and examine their basic properties.
• be able of applying the basic techniques, results and concepts of the course in concrete situations.

CC4019 - ECTS The goal of this course is to serve as an introduction to information theory. Information theory is the study of what information is, and how it can be stored and transmitted. This raises three fundamental questions: Compression: How can we store information using the least possible amount of space? Error-correction: How can we transmit information reliably, over an imperfect communication channel that is prone to errors? Encryption: How can we transmit information privately over a public communication channel? This course will deal with the first two questions. The last one is covered in the cryptography course offered by our department.

CC4015 - ECTS

Provide the student experience in the use, administration and programming of some of the systems / applications currently used in the Windows environment. The particular focus is on event-driven programming using the programming environment of Visual Basic for Applications.

M4031 - ECTS

The course presents the main concepts and techniques of digital image processing and analysis. The main goal is that in the end of the course the students will be able to plan and implement algorithms for information extraction from images.

The course orientation focus on the understanding of concepts and methods, and its effective use in synthetic and experimental data analysis. The course makes an extensive use of advance computational tools (MATLAB).

M4076 - ECTS

It is intended that the students learn the paradigm of computational simulation based on Monte Carlo methods, namely MCMC, as well as the principles of numerical linear algebra, in a framework of critical application as well as their application in interdisciplinary areas.

M4004 - ECTS Upon completion of this curricular unit, the student should:

— master the concepts, methods and results presented, on cryptography and on cryptanalysis, and some of its applications;
— be able to analyze and solve problems of Cryptology, using the methods and results that best apply to the problem under study;
— have adequate preparation to conduct studies and research in areas of mathematics that integrate or use Cryptology;
— be able to communicate, in an efficient manner, his or hers own solutions to problems, and the various topics lectured.

CC4024 - ECTS Identification and application of data mining techniques to extract knowledge from different data sources (e.g. transactions, web, text).

CC4074 - ECTS Students should:
1. Get acquainted with the main supervised and unsupervised machine learning methods for analytics and decision support.
2. Learn how to formalize optimization models for prescriptive analytics using mathematical programming.
3. Get acquainted with languages and libraries for solving these problems.
4. Be able to critically analyze solutions obtained.

M4063 - ECTS

Introduce the main concepts and methods of supervised and unsupervised classification.

M4015 - ECTS 1. To provide the students with advanced regression techniques, including analyses of repeated measurements and analysis of longitudinal data, for continuous and discrete responses, and analyses of survival data
2. Implement statistical analyses in suitable software
3. Promote critical thinking in a data analysis process (data collection, modeling, interpretation of results, ...)

M4049 - ECTS

The main objective of the course is to introduce in a rigorous way the fundamentals of Game Theory, with particular emphasis on Nash equilibria.

M4059 - ECTS To introduce the fundamental concepts and principles of risk theory.
To provide a fundamental knowledge of the commonly used stochastic models and techniques in non-life insurance mathematics.

CC4020 - ECTS To improve background on techniques for designing algorithms and analysing their correctness and complexity.
To know and apply methods for finding exact and approximate solutions for hard problems.

M5009 - ECTS

M5007 - ECTS

M4062 - ECTS

M4122 - ECTS Domain of the most relevant computational methods and principles underlying modern statistical  analysis and inference and application to the analysis of several types of data.

M4082 - ECTS To become familiar with the research and selection of  scientific and technical references, to analyse and discuss scientific papers and to acquire mathematical communication skills, both oral and written.

M4113 - ECTS The aim of this course is to introduce the students to time series analysis methods.

M4081 - ECTS

Upon successful completion of this course, the student will:

• Know most of the classical examples of error correcting codes;
• be able of reproducing key results of the theory and give rigorous and detailed proofs of them.
• be able of constructing new codes from old ones and examine their basic properties.
• be able of applying the basic techniques, results and concepts of the course in concrete situations.

CC4019 - ECTS The goal of this course is to serve as an introduction to information theory. Information theory is the study of what information is, and how it can be stored and transmitted. This raises three fundamental questions: Compression: How can we store information using the least possible amount of space? Error-correction: How can we transmit information reliably, over an imperfect communication channel that is prone to errors? Encryption: How can we transmit information privately over a public communication channel? This course will deal with the first two questions. The last one is covered in the cryptography course offered by our department.

M4031 - ECTS

The course presents the main concepts and techniques of digital image processing and analysis. The main goal is that in the end of the course the students will be able to plan and implement algorithms for information extraction from images.

The course orientation focus on the understanding of concepts and methods, and its effective use in synthetic and experimental data analysis. The course makes an extensive use of advance computational tools (MATLAB).

M4004 - ECTS Upon completion of this curricular unit, the student should:

— master the concepts, methods and results presented, on cryptography and on cryptanalysis, and some of its applications;
— be able to analyze and solve problems of Cryptology, using the methods and results that best apply to the problem under study;
— have adequate preparation to conduct studies and research in areas of mathematics that integrate or use Cryptology;
— be able to communicate, in an efficient manner, his or hers own solutions to problems, and the various topics lectured.

CC4024 - ECTS Identification and application of data mining techniques to extract knowledge from different data sources (e.g. transactions, web, text).

CC4074 - ECTS Students should:
1. Get acquainted with the main supervised and unsupervised machine learning methods for analytics and decision support.
2. Learn how to formalize optimization models for prescriptive analytics using mathematical programming.
3. Get acquainted with languages and libraries for solving these problems.
4. Be able to critically analyze solutions obtained.

M4063 - ECTS

Introduce the main concepts and methods of supervised and unsupervised classification.

M4015 - ECTS 1. To provide the students with advanced regression techniques, including analyses of repeated measurements and analysis of longitudinal data, for continuous and discrete responses, and analyses of survival data
2. Implement statistical analyses in suitable software
3. Promote critical thinking in a data analysis process (data collection, modeling, interpretation of results, ...)

M4049 - ECTS

The main objective of the course is to introduce in a rigorous way the fundamentals of Game Theory, with particular emphasis on Nash equilibria.

M4059 - ECTS To introduce the fundamental concepts and principles of risk theory.
To provide a fundamental knowledge of the commonly used stochastic models and techniques in non-life insurance mathematics.

CC4020 - ECTS To improve background on techniques for designing algorithms and analysing their correctness and complexity.
To know and apply methods for finding exact and approximate solutions for hard problems.