Department of Computer Science
Professional area: Computing and Computer Science
Speciality: Data Science
Awarded qualification: Data Analyst
Level of qualification: Master (M.Sc)
Length of programme: 1.5 year (3 semesters)
Number of credits:
90 credits
Field(s) of study (ISCED-F): 0613: Software and applications development and analysis (11.3, 11.4 - 481)
Specific admission requirements: Completed bachelor or master degree program and after entrance exam.
Candidates take an exam - interview (for candidates who obtained a bachelor's degree in one of the following professional fields: computer science; informatics, business informatics, computer systems and technology or software engineering) and a test (for graduates of other professional fields).
Training in the specialty is entirely in English, which is why applicants also submit a language proficiency document.
Qualification requirements and regulations, including graduation requirements:
In order to get their qualification students must be allocated 90 credits Graduation requirements: Development and defense of a diploma thesis.
Profile of the programme:
The Master's program Data Science offers specialized training in current issues of Computer science in accordance with international, European and national criteria and requirements and needs of professionals in the field of data science.
The training of students in this program is conducted in English only in full-time or part-time training. The subjects in the curriculum are divided into: compulsory, optional and elective.
Programme learning outcomes:
As a result of the training, students acquire:
Specific knowledge in computer science and management: programming and algorithms, business process automation, data engineering, computer vision, data mining, neural networks, machine learning, artificial intelligence algorithms, specific statistical methods, distributed and cloud computing, international standards and methods for team and project management.
The practical skills acquired by students are oriented towards: experimenting with data, designing and planning data-driven research, established and new practices for solving typical tasks with artificial intelligence, tailored to the needs of different groups of users and in accordance with established in the organization business processes, design and implementation of digitization and digital business transformation processes, quick orientation in a specific IT business environment and application of international standards and practices for team leadership and software project management.
In accordance with the European competence framework and the National Qualification Framework, the education of students in the "Data Science" specialty stimulates the development of transferable competences for: teamwork, work in a digital and virtual environment, work in mixed international and interdisciplinary teams, innovative thinking, creation and application of new technologies in solving various problems.
Programme structure diagram with credits *:
№ |
ECTS Code |
Course Title |
Lectures and seminars |
Out-of-class workload |
Number of credits |
1 |
46-702 |
Programming and Algorithms |
90 |
180 |
9 |
2 |
46-703 |
Data Engineering |
60 |
120 |
6 |
3 |
46-705 |
Computer Vision |
60 |
120 |
6 |
4 |
46-706 |
Teams Leadership |
30 |
60 |
3 |
5 |
46-708 |
Business Process Automation |
30 |
60 |
3 |
Total for semester I |
|
|
30 |
||
1 |
46-817 |
Master Class |
30 |
60 |
3 |
2 |
46-716 |
Data Mining |
180 |
360 |
18 |
3 |
|
Elective Course 1 |
60 |
120 |
6 |
4 |
|
Elective Course 2 |
60 |
120 |
6 |
Total for semester II |
|
|
30 |
||
1 |
Optional Course |
30 |
90 |
4 |
|
2 |
46-707 |
Distributed and Cloud Computing |
60 |
90 |
5 |
3 |
46-722 |
Electronic sports |
0 |
60 |
2 |
4 |
46-901 |
Research and Development Internship |
40 |
80 |
4 |
5 |
|
Master Thesis Development |
|
450 |
15 |
|
|
Total for semester III |
|
|
30 |
|
|
Total for the entire course of study: |
|
|
90 |
* In Varna Free University, a credit equals 30 lessons, of which 10 contact hours (lectures and seminars) and 20 hours independent work.
Mode of study:
distance learning
Examination regulations and grading scale: The regulations are specific to each course (project or task; individual or group assignments, research papers, tests, project assignment, etc.).
Obligatory or optional mobility windows: Students can participate in Erasmus student mobility, which enables them to get to know European practices and to receive training for a successful career in international teams.
Work-based learning: Students in the Master's program will have the opportunity during their education to participate in a number of initiatives with Bulgarian and foreign companies to support their achievement through new contacts, provocations, competitions, as well as master classes organized by the Department. Additionally, it will be given the opportunity to acquire professional certifications in the field.
Occupational profiles of graduates:
Successful graduates can work effectively as data scientists, data analysts, database administrators, data integrators, database architects, data quality assurance, data engineers, software engineers, information management experts, experts in business intelligent analysis, manager at data centers and others.
Access to further studies: Graduates can enter PhD programmes.
Head of Department:
Assist. Prof. Antonina Ivanova
e-mail: antonina.ivanova@vfu.bg
Contacts with Department of Computer Science
Secretary: Galina Peneva
Tel.: +359-52 359572;
е-mail: cse@vfu.bg, galina.peneva@vfu.bg
To apply for the master program contact the university admission center:
admission@vfu.bg