Digital modellingLaajuus (3 cr)
Code: KL25AB55000
Objective
Students will be able to represent real-world processes using mathematical models and numerical computing software. They will also be able to utilise mathematical models in the designing of control software for automation devices.
Content
Modelling, simulation, interpolation, fuzzy logic, factor analysis, principal component analysis, structured text programming, MATLAB and Simulink.
Qualifications
No previous studies are required.
Assessment criteria, satisfactory (1)
Satisfactory (1-2): The student knows basics.
Assessment criteria, good (3)
Good (3-4): The student masters well principles of mathematical modelling and can utilize models in the designing of control software for automation devices.
Assessment criteria, excellent (5)
Excellent (5): The student can utilize learned skills in demanding projects.
Materials
Lecture material and demonstrations
Enrollment
14.11.2022 - 15.01.2023
Timing
09.01.2023 - 26.02.2023
Credits
3 op
Teaching languages
- Finnish
Degree programmes
- Bachelor of Engineering, Automation Engineering
Teachers
- Pasi Mikkonen
Student groups
-
AUTE21SA
Objective
Students will be able to represent real-world processes using mathematical models and numerical computing software. They will also be able to utilise mathematical models in the designing of control software for automation devices.
Content
Modelling, simulation, interpolation, fuzzy logic, factor analysis, principal component analysis, structured text programming, MATLAB and Simulink.
Materials
Lecture material and demonstrations
Teaching methods
Lectures, exercises
Employer connections
None
Student workload
81 h
Evaluation scale
1-5
Assessment criteria, satisfactory (1)
Satisfactory (1-2): The student knows basics.
Assessment criteria, good (3)
Good (3-4): The student masters well principles of mathematical modelling and can utilize models in the designing of control software for automation devices.
Assessment criteria, excellent (5)
Excellent (5): The student can utilize learned skills in demanding projects.
Assessment methods and criteria
Assignments
Qualifications
No previous studies are required.
Enrollment
16.04.2022 - 07.09.2022
Timing
29.08.2022 - 16.10.2022
Credits
3 op
Teaching languages
- Finnish
Degree programmes
- Bachelor of Engineering, Automation Engineering
Teachers
- Pasi Mikkonen
Student groups
-
AUTE20SA
Objective
Students will be able to represent real-world processes using mathematical models and numerical computing software. They will also be able to utilise mathematical models in the designing of control software for automation devices.
Content
Modelling, simulation, interpolation, fuzzy logic, factor analysis, principal component analysis, structured text programming, MATLAB and Simulink.
Materials
Lecture material and demonstrations
Teaching methods
Lectures, exercises
Employer connections
None
Student workload
81 h
Evaluation scale
1-5
Assessment criteria, satisfactory (1)
Satisfactory (1-2): The student knows basics.
Assessment criteria, good (3)
Good (3-4): The student masters well principles of mathematical modelling and can utilize models in the designing of control software for automation devices.
Assessment criteria, excellent (5)
Excellent (5): The student can utilize learned skills in demanding projects.
Assessment methods and criteria
Assignments
Qualifications
No previous studies are required.
Enrollment
03.12.2021 - 23.01.2022
Timing
10.01.2022 - 29.05.2022
Credits
3 op
Teaching languages
- Finnish
Degree programmes
- Bachelor of Engineering, Automation Engineering
Teachers
- Pasi Mikkonen
Student groups
-
MAUTE19
Objective
Students will be able to represent real-world processes using mathematical models and numerical computing software. They will also be able to utilise mathematical models in the designing of control software for automation devices.
Content
Modelling, simulation, interpolation, fuzzy logic, factor analysis, principal component analysis, structured text programming, MATLAB and Simulink.
Materials
Lecture material and demonstrations
Teaching methods
Lectures, exercises
Employer connections
None
Student workload
81 h
Evaluation scale
1-5
Assessment criteria, satisfactory (1)
Satisfactory (1-2): The student knows basics.
Assessment criteria, good (3)
Good (3-4): The student masters well principles of mathematical modelling and can utilize models in the designing of control software for automation devices.
Assessment criteria, excellent (5)
Excellent (5): The student can utilize learned skills in demanding projects.
Assessment methods and criteria
Assignments
Qualifications
No previous studies are required.