Course of Study Computational Science and Engineering (Study Cohort w17)

Sample course plan M  Master Computational Science and Engineering (IIWMS)
Specialisation Scientific Computing
Legend:
Core qualification CompulsorySpecialisation CompulsoryFocus CompulsoryThesis Compulsory
Core qualification Elective CompulsorySpecialisation Elective CompulsoryFocus Elective CompulsoryInterdisciplinary complement
LP
Semester 1FormHrs/wk
Semester 2FormHrs/wk
Semester 3FormHrs/wk
Semester 4FormHrs/wk
1
Efficient Algorithms
Efficient AlgorithmsVL2
Efficient AlgorithmsUE2
High-Performance Computing
Fundamentals of High-Performance ComputingVL2
Fundamentals of High-Performance ComputingPBL2
Research Project and Seminar
SeminarSE2
Project WorkPK10
Master Thesis
2
3
4
5
6
7
Hierarchical Algorithms
Hierarchical AlgorithmsVL2
Hierarchical AlgorithmsUE2
Approximation and Stability
Approximation and StabilityVL3
Approximation and StabilityUE1
8
9
10
11
12
13
Matrix Algorithms
Matrix AlgorithmsVL2
Matrix AlgorithmsUE2
Numerical Mathematics II
Numerical Mathematics IIVL2
Numerical Mathematics IIUE2
14
15
16
17
18
19
Matrix Theory
Numerical Analysis and Matrix TheoryVL2
Numerical Analysis and Matrix TheoryUE2
Numerical Treatment of Ordinary Differential Equations
Numerical Treatment of Ordinary Differential EquationsVL2
Numerical Treatment of Ordinary Differential EquationsUE2
Scientific Computing and Accuracy
Verification MethodsVL2
Verification MethodsUE2
20
21
22
23
24
25
Numerics of Partial Differential Equations
Numerics of Partial Differential EquationsVL2
Numerics of Partial Differential EquationsUE2
26
27
28
29
30
Business & Management (from catalogue) - 6LP
Nontechnical Elective Complementary Courses for Master (from catalogue) - 6LP

The choice of courses from the catalogue is flexible (depends on the semestral work load), provided the necessary number of required credits is reached.