Tables of courses for Graduate Program of Computer Sciences

 | Post date: 2021/06/23 | 
The Tables of Courses of Computer Science are as follows:
 
Table No. 1-1: Compulsory courses in logic and formal methods branches:
No Course Units
1 Computational data mining 3
2 Advanced algorithms 3
3 Model checker 3

 
Table No. 1-2: Specialized – optional courses of official languages ​​branch and formal methods:
No Course Units Hours/ theory Hours/applied Total hours Prerequisites or simultaneous courses
1 Model checker 3 48   48  
2 Automatic proof 3 48   48  
3 Logic programming 3 48   48  
4 Formal semantics 3 48   48  
5 Formal description of software 3 48   48  
6 Software authentication 3 48   48  
7 Special topics in formal methods 3 48   48 Lecturer  permission
The student is required to take at least 6 units of the courses in Table 2-1.
The student must take two of the courses in Tables 1-1 to7-1 or 1-2 to7-2 or one of the related master's degree courses according to the group advice.

 
Table No2-1: Compulsory courses in the field of scientific computing:
No Course Units
1 Computational data 3
2 Advanced algorithms 3
3 Matrix computations 3

 
Table 2-2: Specialized – optional courses of scientific computations.
No Course Units Hours / theory Hours/ applied Total hours Prerequisites or simultaneous courses
1 Advanced math software 3 48   48 Numerical analysis 1
2 Linear numerical programming 3 48   48 Linear algebra
3 Nonlinear-numerical optimization 3 48   48 Numerical linear algebra or numerical analysis 1 or matrix computations
4 Advanced linear programming 3 48   48 Linear numerical programming or instructor permission
5 Advanced nonlinear optimization 3 48   48 Numerical linear algebra or numerical analysis 1 or matrix calculations or group permission
 
 
6 Numerical Integral and differential equations 3 48   48 Numerical analysis 1
7 Numerical partial differential equations 3 48   48 Numerical analysis 1
8 Sparse matrices technology 3 48   48 Numerical linear algebra or matrix calculations or instructor permission
91 Modeling and geometric design 3 48   48 Numerical linear algebra or matrix calculations or instructor permission
11 Integer programing and networking 3 48   48 Numerical algebra, or numerical linear programming, or instructor permission
12 Combinatory optimization 3 48   48 Numerical algebra, or numerical linear programming, or instructor permission
13 Parallel algorithms for scientific computing 3 48   48 Numerical analysis 1 or instructor permission
14 Numerical stochastic differential equations 3 48   48 Numerical analysis 1 or instructor permission
15 Numerical stochastic partial differential equations 3 48   48 Ordinary stochastic differential equations, Simulation
16 Simulation 3 48   48 Probability theory and stochastic processes, statistics
17 Special topics in scientific computing
 
3 48   48 Instructor permission
The student is required to take at least 6 units of the courses in Table 2-2.
The student must take two of the courses in Tables 1-1 to 7-1 or 1-2 to 7-2 or one of the related master's degree courses according to the group advice.


 
Table No. 3-1: Compulsory courses in Algorithm branch and theory of computations:
No Course Units
1 Computational data 3
2 Advanced algorithms 3
3 Advanced theory of computation 3
 
 
Table No. 3-2: Specialized-optional courses in computational theory:
Course code Course Units Hours/ theory Hours/ applied Total hours Prerequisites or simultaneous courses
1 Recursion theory and computability 3 48   48 Instructor permission
2 Computation complexity 3 48   48  
3 Advanced computation complexity 3 48   48  
4 Parallel algorithms 3 48   48  
5 Stochastic algorithms 3 48   48  
6 Design and analysis of algorithms 3 48   48  
7 Fundamentals of cryptography theory 3 48   48  
8 Games theory 3 48   48  
9 Advanced graph theory 3 48   48 Graphs and algorithms
10 Combinatorial algorithms 3 48   48  
11 Graphs and algorithms 3 48   48  
12 Approximate algorithms 3 48   48  
13 Computational geometry 3 48   48  
14 combinatorics 3 48   48 Combinatorial analysis 1
15 Structural compounds 3 48   48  
16 Computational analysis 3 48   48 Mathematical logic, Mathematical analysis
17 Special Topics in computational theory 3 48   48 Instructor permission
The student is must take at least 6 units of the courses from Table 2-3
The student must take two of the courses in Tables 1-1 to 7-1 or 2-1 to 7-2 or one of the related master's degree courses, depending on the group advice.


 
Table 4-1: Compulsory courses in soft computing and artificial intelligence.
No Course Units
1 Computational data 3
2 Advanced algorithms 3
3 Advanced artificial intelligence 3 3


 
Table No. 4-2: Specialized- optional courses - Soft computing and artificial intelligence:
Course code Course Units Hours/ theory Hours/applied Total hours Prerequisites or simultaneous courses
1 Soft computing 3 48   48 -
2 Advanced artificial intelligence 3 48   48 -
3 Expert systems 3 48   48 -
4 Machine learning 3 48   48 -
5 Natural languages processing 3 48   48 -
6 Statistical Machine learning 3 48   48 Machine learning
7 Discrete dynamic systems 3 48   48 -
8 Intelligent algorithms 3 48   48 -
9 Multi agent systems 3 48   48 -
10 Deep learning 3 48   48 Machine learning
11 Data mining 3 48   48 -
12 Advanced network optimization 3 48   48 -
13 Special Topics in Artificial Intelligence 3 48   48 Instructor permission
14 Special Topics in Soft Computing 3 48   48 Instructor permission
The student is required to take at least 6 units of the courses in Table 4-2.
The student must take two of the courses in Tables 1-1to 7-1 or 1-2 to 7-1, or one of the related master's degree courses according to the group advice.

 
Table 5-1: Compulsory courses in systems theory:
No Course Units
1 Computational data mining 3
2 Advanced algorithms 3
3 Advanced software design 3


 
Table No. 5-2: Specialized-optional courses in systems theory:
Course code Course Units Hours/theory Hours/ applied Total hours Prerequisites or simultaneous courses
1 Advanced software design 3 48   48 -
2 Advanced agent system 3 48   48 -
3 Advanced data base 3 48   48 -
4 Real time systems 3 48   48 -
5 Decision support systems 3 48   48 -
6 Advanced compiler 3 48   48 -
7 Distributed systems 3 48   48 Artificial intelligence
8 Advanced computer networks 3 48   48 -
9 Special Topics in Systems Theory 3 48   48 Instructor permission
The student is required to take at least 6 units of the courses in Table 5-2. advice.


 
Table No. 6-1: Compulsory courses in Decision Science and Knowledge:
No Course Units
1 Computational data mining 3
2 Advanced algorithms 3
3 Convex optimization
 
3


 
Table No 6-2: Specialized-optional Courses in Decision Science and Knowledge:
Course code Course Units Hours/theory Hours/applied Total hours Prerequisites or simultaneous courses
1 Decision with multiple criteria 3 48   48 Operations Research
2 Soft computing 3 48   48 -
3 Machine learning 3 48   48 -
4 Information and uncertainty 3 48   48 -
5 Fuzzy decision systems 3 48   48 Decision with multiple criteria
6 Learning mathematics 3 48   48 -
7 Combinatorial optimization 3 48   48 -
8 Stochastic processes 3 48   48 -
9 Probability and fuzzy statistics 3 48   48 Soft computing
10 Games theory 3 48   48 -
11 Transcendental optimization 3 48   48 Operational research
12 Data mining 3 48   48 -
13 Advanced data mining 3 48   48 Data mining
14 Text mining & web mining 3 48   48 Data mining
15 Artificial Neural Networks 3 48   48 Mathematical optimization or Instructor permission
16 Multi agent systems 3 48   48 -
17 Special topics in decision science and knowledge 3 48   48 Instructor permission
The student is required to take at least 6 units of the courses in Table 2-6.
The student must take two of the courses in Tables 1-1 to 7-1 or 1-2to 7-1, or one of the related master's degree courses, depending on the group permission.

 
Table 7-1: Compulsory courses of Data Mining branch:
No Course units
1 Computational data mining 3
2 Advanced algorithms 3
3 Data mining 3
 

 
Table 7-2: Specialized-optional courses in data mining branch:
Course code Course Units Hours/ theory Hours/applied Total hours Prerequisites or simultaneous courses
1 Learning mathematics 3 48   48 -
2 Convex optimization 3 48   48 -
3 Combinatorial optimization 3 48   48 -
4 Machine learning 3 48   48 -
5 Statistical machine learning 3 48   48 Machine learning
6 Advanced data mining 3 48   48 Data mining
7 Text mining and web mining
 
3 48   48 Data mining
8 Feature selection and feature extraction 3 48   48 Data mining or Instructor permission
9 Graph mining 3 48   48 Data mining or Instructor permission
10 Probabilistic graph models 3 48   48 Data mining or Instructor permission
11 Complex Networks  3 48   48 Data mining or Instructor permission
12 Data visualization 3 48   48 Data mining or Instructor permission
13 Outlier detection 3 48   48 Data mining or Instructor permission
14 Modeling and data processing 3 48   48 Data mining
15 Deep learning 3 48   48 Machine learning
16 Special topics in data mining 3 48   48 Instructor decision
The student is required to take at least 6 units of the courses in Table 7-2.
The student must take two of the courses in Tables 1-1to 7-1 or 1-2to 7-2, or one of the related master's degree courses, depending on the group permission.

 

 



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