ChineseMSc in Computer Science Engineering
Faculty of Mechanical, Electrical Engineering and Informatics
| Name of qualification and level | Duration of studies | Intake | Necessary no. credits for degree | Tuition fee | Application fee | Supervisor | Programme mentor |
|---|---|---|---|---|---|---|---|
| Computer Science Engineer (MSc) | 4 semesters – full time programme | September | 120 credits | 2,600 EUR / semester | 100 EUR / application |
Dr Katalin Kovács |
László Lili Katalin |
The Computer Science Engineering MSc programme will equip students with knowledge of algorithms, performance and quality of IT services, communications systems protocols and architectures, a safe and secure design of hardware and software components of embedded and distributed systems, and also to combine a scientific perspective with the practical engineering approaches. Advanced and emerging future technologies, such as Artificial Intelligence methods are in special focus. As a basic objective, the students will be prepared to be able to continue their studies in postgraduate schools, such as in the Multidisciplinary Doctoral School of Engineering Sciences at Széchenyi István University.
Structure of studies
The total number of credits needed to complete the programme is 120 credits. The courses of the programme are divided into six categories: basic knowledge of natural sciences (20 credits), knowledge of economics and human sciences (9 credits), professional core material (33 credits), differentiated professional knowledge (22 credits), optional subjects (6 credits), thesis work (30 credits). 1 credit equals one ECTS credit, and 1 credit is defined as 25 student working hours.
Language requirements
TOEFL 513 / IELTS 5.5 /oral examination, TOEFL IBT test score of 66 or any standardised international English language exam corresponding with Hungarian B2 at the Bachelors level and C1 at Masters level.
If there is no standardised English exam, the University relies on an online interview. Applicants not complying with language requirements must enrol in a preparatory language programme. After having completed the language course and passed the requisite final examination, if there are no professional reservations on the part of the Faculty, admission to the selected Bachelor's programme is automatic.
Academic requirements
Completed and signed application form, copy of your passport, notarized copy of Bachelor’s degree relevant to the Master's studies, notarized copy of the Transcript of Records, notarized copy of your language certificate, recent photograph, Curriculum Vitae (resumé) in English, Motivational Letter in English, Academic Reference letter in English (Issued by your former academic institution/teacher)
Who is the programme aimed at?
The MSc program is designed for students and professionals holding bachelor degrees (BSc) in diverse areas of engineering and sciences who desire to further their career by adding new knowledge, tools and skills from a cross-disciplinary perspective with a strong focus on improving skills necessitated by research. The program is designed to accommodate full-time students only.
Details
Compulsory courses:
|
Nr. |
Neptun code of course |
Name of course |
lessons / week |
seminars / week |
assessment type |
credit points |
semester |
|---|---|---|---|---|---|---|---|
|
1 |
Logic |
2 |
2 |
v |
5 |
1 |
|
|
2 |
IT Project Management |
2 |
2 |
v |
4 |
1 |
|
|
3 |
Theory of Algorithms |
2 |
2 |
v |
5 |
1 |
|
|
4 |
Data Analysis |
4 |
0 |
v |
4 |
1 |
|
|
5 |
Management Competencies |
2 |
2 |
f |
5 |
1 |
|
|
6 |
Automatic Controls |
2 |
0 |
v |
5 |
2 |
|
|
7 |
Formal Languages and Automata |
4 |
0 |
v |
4 |
2 |
|
|
8 |
System and Software Testing |
2 |
2 |
v |
4 |
2 |
|
|
9 |
Coding Theory |
4 |
0 |
v |
5 |
2 |
|
|
10 |
Advanced Corporate Finance |
0 |
2 |
v |
4 |
2 |
|
|
11 |
Thesis Consultation I. (Master Programme) |
0 |
0 |
f |
15 |
3 |
|
|
12 |
Professional Practice |
0 |
0 |
a |
0 |
3 |
|
|
13 |
Numerical Analysis |
2 |
2 |
v |
5 |
3 |
|
|
14 |
Knowledge Base Technologies and Planning |
1 |
2 |
v |
4 |
4 |
|
|
15 |
Optimization of Discrete Systems |
2 |
2 |
v |
4 |
4 |
|
|
16 |
Compilers |
2 |
2 |
v |
4 |
4 |
|
|
17 |
Thesis Consultation II. (Master Programme) |
0 |
0 |
f |
15 |
4 |
Hungarian Language (compulsory)
|
Nr. |
Neptun code of course |
Name of course |
lessons / week |
seminars / week |
assessment type * |
credit points |
|---|---|---|---|---|---|---|
|
1 |
Hungarian Language and Culture 1. |
0 |
3 |
a |
0 |
|
|
2 |
Hungarian Language and Culture 2. |
0 |
3 |
a |
0 |
Free optional courses
6 credit points should be obtained from this group of courses.
|
Nr. |
Neptun code of course |
Name of course |
lessons / week |
seminars / week |
assessment type * |
credit points |
|---|---|---|---|---|---|---|
|
1 |
Nanoelectronics |
2 |
0 |
v |
3 |
|
|
2 |
Measuring Theories and Techniques |
2 |
2 |
v |
5 |
|
|
3 |
Nuclear Technology |
2 |
0 |
v |
2 |
|
|
4 |
Risk Analysis |
2 |
0 |
f |
5 |
|
|
5 |
Exchange Course 2. |
0 |
0 |
f |
3 |
|
|
6 |
Leadership and Organizational Communication |
2 |
2 |
v |
5 |
|
|
7 |
Innovation and Research Communication I. |
0 |
0 |
f |
5 |
|
|
8 |
Innovation and Research Communication II. |
0 |
0 |
f |
5 |
Differentiated professional courses
22 credit points should be obtained from this group of courses.
|
Nr. |
Neptun code of course |
Name of course |
lessons / week |
seminars / week |
labs / week |
assessment type * |
credit points |
|---|---|---|---|---|---|---|---|
|
1 |
Interface Technologies |
2 |
2 |
0 |
v |
5 |
|
|
2 |
Design of Virtual Instrument |
2 |
0 |
1 |
v |
5 |
|
|
3 |
Photometry and Colorimetry |
2 |
2 |
0 |
v |
4 |
|
|
4 |
Computer Image Analysis |
2 |
2 |
0 |
v |
4 |
|
|
5 |
Modern Technologies of System Development |
2 |
0 |
0 |
v |
3 |
|
|
6 |
Adaptive Systems |
3 |
0 |
0 |
v |
4 |
|
|
7 |
Computational Intelligence |
2 |
2 |
0 |
v |
5 |
|
|
8 |
Software Examination |
3 |
0 |
0 |
v |
4 |
|
|
9 |
Introduction to Bioinformatics |
3 |
0 |
0 |
v |
4 |
|
|
10 |
Complexity Theory |
3 |
0 |
0 |
v |
4 |
|
|
11 |
Document Management Systems |
2 |
0 |
0 |
v |
3 |
|
|
12 |
Data Mining |
2 |
1 |
0 |
v |
4 |
|
|
13 |
Platform-Independent Programming |
2 |
1 |
0 |
v |
4 |
|
|
14 |
Programming in LabView |
0 |
3 |
0 |
v |
4 |
|
|
15 |
Stochastic Processes |
2 |
2 |
0 |
v |
4 |
|
|
16 |
Parallel Programming |
1 |
2 |
0 |
v |
4 |
|
|
17 |
Information Security |
2 |
0 |
2 |
v |
5 |
|
|
18 |
Internet of Things |
3 |
0 |
1 |
v |
5 |
|
|
19 |
Cloud Computing |
2 |
0 |
2 |
f |
5 |
* type of assessment
f - evaluation based on student’s performance and work during the semester
v - evaluation based on student’s exam grade in a 5-grade system: excellent (5) – good (4) – satisfactory (3) – passed (2) – fail (1)
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