Maestría en Sistemas Computacionales
Program director
Luis Julián Domínguez Pérez, Ph.D
Doctor of Philosophy from Dublin City University (DCU), Master in Quality from the Institute of Higher Studies of Tamaulipas (IEST-Anáhuac), Master in Information Security from the University of La Rioja (UNIR) and Computer Systems Engineer from IEST-Anáhuac; he carried out his postdoctoral stays at CINVESTAV IPN and LTI.
His areas of interest include post-quantum cryptography, elliptic curves, and information security. He is a member of the IEEE, AMEXCOMP, IACR, and SMM.
Reasons to study
this master's degree
You enter a project that combines theory and practice for problem-solving, focused on developing skills and good programming practices.
You link your professional practice with technology-based companies and from the beginning of the master's program you participate in projects that seek to solve industry problems.
You receive support from an academic body whose members are part of the National System of Researchers, specializing in high-performance systems.
A program built for professionals like you
This master's degree program is open to professionals:
- Graduates of Computer Systems Engineering, Computing, Information Technologies, Computer Networks or other related fields, with skills in computer systems programming.
- They have worked in research, development, administration, consulting and teaching activities in computer science, in any sector of the economy such as industry, commerce, services, the social sector and government.
- Programmers, analysts, and developers who provide information management and analysis services.
- They have developed computer systems and want to delve deeper into the methodologies for developing these systems geared towards industry.
- From educational institutions where computer systems are the object of study.
Upon completion of the master's program you will be able to:
- Analyze, design and implement efficient algorithms for the analysis and processing of massive amounts of information (Big Data), as well as model and analyze high-performance systems.
- To propose efficient computational solutions.
- Design and implement algorithms for searching and analyzing massive datasets.
- Create large-scale systems and applications based on web services or mobile technology.
- Implement the most important techniques of machine learning and deep learning for solving problems involving classification and prediction applied to text, images, audio and structured information.
- Develop solutions that use some of the following technologies: R, Python, Java, Android Studio, DirectX, OpenGL, TensorFlow, Amazon Web Services (AWS), MongoDB, Hadoop, MapReduce, Cassandra, Neo4J, among others.
