M4083 - ECTS

1. Train the student for regression analysis involving  responses following a distribution from the exponencial family (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,...)

M4142 - 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.

M4061 - ECTS

Acquire a solid knowledge in inductive statistics and develop capacities and skills in statistical modelling techniques, fundamental to the presentation, analysis and interpretation of data sets.

M4063 - ECTS

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

M4042 - ECTS

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;
• Reproduce key results of the theory and give rigorous and detailed proofs of them.
• Construct new codes from old ones and examine their basic properties.
• Apply the basic techniques, results and concepts of the course to concrete examples and exercises.

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.

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.

CC4015 - ECTS

Provide students with experience in using, administering, and programming some of the most commonly used systems/applications in the Windows environment. The particular focus will be on the event-driven programming paradigm using the programming environment of Visual Basic for Applications coupled with data manipulation 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 focus on the understanding of concepts and methods, and its effective use in synthetic and experimental data analysis. The course makes an intensive 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.

CC4024 - ECTS Identification and application of data mining techniques for knowledge extraction from various data sources. The focus will be on association rules, sequence mining, recommendation systems, link analysis, information retrieval, and text mining.

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.

M4056 - ECTS

The main objective of the course is to introduce rigorously the main concepts of Mathematical Finance in discrete and continuous time. Those concepts and the relevant mathematical tools to their analysis will be considered in the course.

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

Introduction to stochastic processes.Tools for the analysis of stochastic processes and its applications in several areas, such as signal processing, information theory, finance and economics, biology and medicine. Special attention to the understanding of the concepts and methods and to its application in interdisciplinary areas using simulated and real data.

M4049 - ECTS This course aims to introduce the foundations with and without uncertainty. The course aims to do a critical analysis of such concepts, recognizing the potential as well as the limitations of game theory as a methodological tool. The main concepts of the area wil be addressed, as well as the most important mathematical tools for their analysis.

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

M5008 - ECTS

M4142 - 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.

M4061 - ECTS

Acquire a solid knowledge in inductive statistics and develop capacities and skills in statistical modelling techniques, fundamental to the presentation, analysis and interpretation of data sets.

M4063 - ECTS

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

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;
• Reproduce key results of the theory and give rigorous and detailed proofs of them.
• Construct new codes from old ones and examine their basic properties.
• Apply the basic techniques, results and concepts of the course to concrete examples and exercises.

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.

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.

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

CC4024 - ECTS Identification and application of data mining techniques for knowledge extraction from various data sources. The focus will be on association rules, sequence mining, recommendation systems, link analysis, information retrieval, and text mining.

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.

M4056 - ECTS

The main objective of the course is to introduce rigorously the main concepts of Mathematical Finance in discrete and continuous time. Those concepts and the relevant mathematical tools to their analysis will be considered in the course.

M4049 - ECTS This course aims to introduce the foundations with and without uncertainty. The course aims to do a critical analysis of such concepts, recognizing the potential as well as the limitations of game theory as a methodological tool. The main concepts of the area wil be addressed, as well as the most important mathematical tools for their analysis.