||Applied Computational Intelligence
||Master in Computer Science
|Standard Length of Studies
(Number of ECTS Credits)
|2 years – 4 semesters – 120 ECTS
|Type of Study
|Higher Education Institution
|Faculty / Department
||Faculty of Mathematics and Computer Science
||Professor Horia F. Pop
||+40 264 405327
||+40 264 591906
|Profile of the Degree Programme
||Applied Computational Intelligence degree program
|Target Group / Addressees
||Graduates in Mathematics, Computer Science, Economics, Electrical/Electronic Engineering, Physics, Chemistry, Biology, etc.
||Graduate student recruitment is achieved by competition. The overall three/four-year undergraduate average grade and a personal portfolio, for candidates with a Bachelor Degree in Computer Science, Computer Mathematics or Economical Computer Science and respectively the grade of a written test (see the curricula here) and a personal portfolio, for candidates outside the above mentioned areas.
|Further Education Possibilities
||The master’s program aims at providing students with the appropriate tools for further doctoral studies and professional activity.
|Description of Study
- Advanced methods in data analysis
- Machine learning
- Statistical methods in computational intelligence
- Knowledge discovery in wide area networks
- Simulation methods
- Scientific data visualization
- Unconventional computation for real world problem solving
- Knowledge based systems and language technology
- Cooperative intelligent agents
- Declarative programming in machine learning
- Applications of computational linguistics
- Applications of computational intelligence in software engineering
|Purposes of the Programme
- Acquisition of theoretical, applicative and practical knowledge of intelligent and computational paradigms inspired from natural science, social and linguistic fields;
- Acquisition of in-depth knowledge in modeling / design / implementation of software applications based on computational intelligence approaches for solving problems specific to natural sciences, economics, industry;
- Acquisition of the mathematical knowledge necessary in order to tackle complex problems;
- Acquisition of specialized knowledge in the analysis and improvement of software processes;
- Professional modeling for team work as well as interdisciplinary approaches to research and development.
|Specialization / Area of Expertise
||Computational intelligence, Mathematical modeling in Computer Science, Intelligent methods in problems solving
||Optional: Practice of Education.
||In the 2nd year (4th semester) of the program the students participate in a research project in the field of Computational intelligence
|Gained Abilities and Skills
- Advanced knowledge of theoretical, methodological, and practical developments in computer science;
- Systematic use of computer science knowledge to model and interpret new situations, within application contexts larger than the known ones;
- Detailed knowledge and integrated use of conceptual and methodological apparatus pertaining to informatics to provide solutions for incompletely defined situations, to solve new theoretical and practical problems;
- Proficient use of verification, validation, and evaluation criteria and methods to his/her own software solutions, ability to formulate value judgments and to justify/explain constructive decisions;
- Use advanced skills to develop and conduct complex software projects, of practical and/or research nature, using a wide range of quantitative and qualitative methods;
- Advanced communication skills within different professional environments, appropriate use of computer science vocabulary, good English knowledge;
- Team work abilities, assuming different execution and leading roles, performing professional tasks with considerable amounts of autonomy and responsibility.
- Demonstrate advanced modeling skills for economic, industrial, scientific phenomena and processes, by using fundamental mathematical, statistical, and computer science knowledge;
- Demonstrate advanced skills to apply intelligent methods for solving real phenomena and to develop and build procedures for efficient use of statistical methods;
- Demonstrate advanced skills to analysis, design, and construction of software systems, using a wide range of hardware / software platforms, programming languages and environments, and modeling, verification and validation tools;
- Demonstrate advanced skills to apply methods for data analysis and processing, data mining, pattern recognition;
- Ability to teach students in high schools computer science concepts and theories, provided that the holder of the dissertation diploma owns a graduation certificate of the pedagogical education module.
|Job Placement, Potential Field of Professional Activity
||Experts in software companies, developer positions, tester positions