Computer Science
Graduation Requirements:
-
Complete the whole curriculum of the program;
-
Complete a thesis and defend it successfully in front of a Committee (Defence result above 5.5 points over 10 points);
-
Complete foreign language proficiency for graduation (detailed information at here).
Program structure in research-oriented:
|
Course code |
Course title |
Credit |
Theory |
Practice Experiment Discussion |
|
A. General courses |
10 |
|
|
|
|
SH700010 |
Philosophy |
3 |
3 |
0 |
|
FL700020 |
Foreign Language |
5 |
5 |
0 |
|
IN700000 |
Research Methodology |
2 |
2 |
0 |
|
B. Compulsory specialized courses |
12 |
|
|
|
|
IT701010 |
Machine Learning |
3 |
3 |
0 |
|
IT701310 |
Data Analysis |
3 |
3 |
0 |
|
IT701350 |
Mathematics for Computer Science |
3 |
3 |
0 |
|
IT701990 |
Master’s Thesis proposal |
3 |
3 |
0 |
|
C. Elective specialized courses |
24 |
|
|
|
|
C.1. Elective courses |
15 |
|
|
|
|
IT701400 |
Digital Image Processing |
3 |
3 |
0 |
|
IT701100 |
Probabilistic Graphical Models |
3 |
3 |
0 |
|
IT701040 |
Distributed Systems |
3 |
3 |
0 |
|
IT701050 |
Information Security |
3 |
3 |
0 |
|
IT701080 |
Knowledge - based Systems |
3 |
3 |
0 |
|
IT701110 |
Cryptography |
3 |
3 |
0 |
|
IT701120 |
Computer Vision |
3 |
3 |
0 |
|
IT701150 |
Mining Massive Data Sets |
3 |
3 |
0 |
|
IT701220 |
Data Mining |
3 |
3 |
0 |
|
IT701200 |
Natural Language Processing |
3 |
3 |
0 |
|
IT701210 |
Spoken Language Processing |
3 |
3 |
0 |
|
IT701240 |
Advanced Topics in Data Science |
3 |
3 |
0 |
|
IT701290 |
Cybersecurity |
3 |
3 |
0 |
|
IT701300 |
Topics in Deep learning |
3 |
3 |
0 |
|
IT701320 |
IoT Application Development |
3 |
3 |
0 |
|
C.2. Elective research topics |
9 |
|
|
|
|
IT701370 |
Research Topic 1 |
3 |
3 |
0 |
|
IT701380 |
Research Topic 2 |
3 |
3 |
0 |
|
IT701390 |
Research Topic 3 |
3 |
3 |
0 |
|
IT701360 |
Research Project |
9 |
9 |
0 |
|
D. Graduation |
|
15 |
|
|
|
IT701000 |
Master's Thesis |
15 |
0 |
15 |
|
Total |
|
61 |
|
|
Program structure in practice-oriented:
|
Course code |
Course title |
Credit |
Theory |
Practice Experiment Discussion |
|
A. General courses |
10 |
|
|
|
|
SH700010 |
Philosophy |
3 |
3 |
0 |
|
FL700020 |
Foreign Language |
5 |
5 |
0 |
|
IN700000 |
Research Methodology |
2 |
2 |
0 |
|
B. Compulsory specialized courses |
15 |
|
|
|
|
IT701010 |
Machine Learning |
3 |
3 |
0 |
|
IT701310 |
Data Analysis |
3 |
3 |
0 |
|
IT701350 |
Mathematics for Computer Science |
3 |
3 |
0 |
|
IT701700 |
Industrial Experience |
6 |
0 |
6 |
|
C. Elective specialized courses |
27 |
|
|
|
|
IT701400 |
Digital Image Processing |
3 |
3 |
0 |
|
IT701100 |
Probabilistic Graphical Models |
3 |
3 |
0 |
|
IT701040 |
Distributed Systems |
3 |
3 |
0 |
|
IT701050 |
Information Security |
3 |
3 |
0 |
|
IT701080 |
Knowledge - based Systems |
3 |
3 |
0 |
|
IT701110 |
Cryptography |
3 |
3 |
0 |
|
IT701120 |
Computer Vision |
3 |
3 |
0 |
|
IT701150 |
Mining Massive Data Sets |
3 |
3 |
0 |
|
IT701220 |
Data Mining |
3 |
3 |
0 |
|
IT701200 |
Natural Language Processing |
3 |
3 |
0 |
|
IT701210 |
Spoken Language Processing |
3 |
3 |
0 |
|
IT701240 |
Advanced Topics in Data Science |
3 |
3 |
0 |
|
IT701290 |
Cybersecurity |
3 |
3 |
0 |
|
IT701300 |
Topics in Deep learning |
3 |
3 |
0 |
|
IT701320 |
IoT Application Development |
3 |
3 |
0 |
|
IT701370 |
Research Topic 1 |
3 |
3 |
0 |
|
IT701380 |
Research Topic 2 |
3 |
3 |
0 |
|
IT701390 |
Research Topic 3 |
3 |
3 |
0 |
|
IT701360 |
Research Project |
9 |
9 |
0 |
|
D. Graduation |
|
9 |
|
|
|
IT701980 |
Master's Project |
9 |
0 |
9 |
|
Total |
|
61 |
|
|
Note: Disscussion 1 credit = 15 theory periods or exercises
= 30 periods of presentation, discussion or practice
