| Language of instruction : English |
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Sequentiality
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No sequentiality
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| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | Master of Software Systems Engineering Technology: specialisatie | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| EC2 - The Master of Software Engineering Technology masters the necessary sets of knowledge and skills regarding the design of integrated, resilient software systems and can creatively conceive, plan and implement them as an integrated part of a series of methodologically ordered actions within multidisciplinary projects with a significant research and/or innovation component. [systems thinking] | | | - DC
| DC-M1 - has knowledge of the basic concepts, structures and coherence. | | | | - BC
| The student can recognize the basic parts of a robot (sensors/actuators) | | | - DC
| DC-M2 - has insight in the basic concepts and methods. | | | | - BC
| The student understands the functionality of the different parts of the robot. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions. | | | | - BC
| The student can select the appropriate sensors for completing a given task. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs. | | | | - BC
| The student can integrate the given sensors/motors into a working robot. | - EC
| EC3 - The Master of Software Engineering Technology has advanced knowledge and understanding of the principles and applications of software engineering, including software development processes, software architectures and the software life cycle, and can apply them, with an understanding of current technological developments, in complex and practice-oriented problem domains. [software engineering] | | | - DC
| DC-M2 - has insight in the basic concepts and methods. | | | | - BC
| The student can design the software architecture for a robot. | | | - DC
| DC-M3 - can recognize problems, plan activities and perform accordingly. | | | | - BC
| The student can identify bottlenecks and problems in the robot software. | | | - DC
| DC-M5 - can analyze problems, logically structure and interpret them. | | | | - BC
| The student can identify sources of bottlenecks or errors and plan activities to correct them. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions. | | | | - BC
| The student can select appropriate methods for communication among the software components of the robot. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs. | | | | - BC
| The student can implement software methods for component-based robot architectures. | - EC
| EC5 - The Master of Software Engineering Technology masters the necessary sets of specialised knowledge and skills for the design of modular, integrated software systems that, on the basis of data acquisition and data analysis, can make intelligent decisions and that are resilient (secure, robust and scalable), within multidisciplinary projects with an applied research and/or innovation component. [intelligent & resilient systems] | | | - DC
| DC-M1 - has knowledge of the basic concepts, structures and coherence.
| | | | - BC
| The student knows basic methods for control, motion planning, robot vision, and task planning. | | | - DC
| DC-M2 - has insight in the basic concepts and methods.
| | | | - BC
| The student understands the differences among methods, as well as the pros and cons of each method. | | | - DC
| DC-M4 - can gather, measure or obtain information and refer to it correctly.
| | | | - BC
| The student can measure the performance of each method and interpret the results. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions.
| | | | - BC
| The student is able to select appropriate methods and algorithms given the task. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs.
| | | | - BC
| The student can implement the appropriate methods and algorithms given the task. | | | - DC
| DC-M8 - can evaluate knowledge and skills critically to adjust own reasoning and course of action accordingly. | | | | - BC
| The student can evaluate the performance of the robot in a given task and adjust components/algorithms to improve it. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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This course focuses on bridging the gap between artificial intelligence and robotic systems. It will explore the basics of a robotic system (sensors, actuators, software etc.), and how artificial intelligence can be used to improve the autonomy of such robotic systems. Part of the course will focus on knowledge representation, reasoning, plannig. In addition, there will be a focus on how one goes from semantic knowledge representations, to actual software implementations that allow the robot to interact with the environment.
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Application Lecture ✔
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Demonstration ✔
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Discussion/debate ✔
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Exercises ✔
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Homework ✔
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Period 1 Credits 4,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory course material |
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All material will be distributed through the electronic learning platform. |
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| Exchange Programme Engineering Technology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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|
This course focuses on bridging the gap between artificial intelligence and robotic systems. It will explore the basics of a robotic system (sensors, actuators, software etc.), and how artificial intelligence can be used to improve the autonomy of such robotic systems. Part of the course will focus on knowledge representation, reasoning, plannig. In addition, there will be a focus on how one goes from semantic knowledge representations, to actual software implementations that allow the robot to interact with the environment.
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Application Lecture ✔
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Demonstration ✔
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Discussion/debate ✔
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|
Exercises ✔
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Homework ✔
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Period 1 Credits 4,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
All material will be distributed through the electronic learning platform. |
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|
| Master of Electronics and ICT Engineering Technology: verbreding | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| EC3 - The holder of the degree has advanced knowledge of and insight in principles and applications of automation and sensor technology and signal processing and can independently recognise, critically analyse and create methodical solutions for complex, practical design or optimisation problems with eye for data processing and implementation, with attention to topical technological developments. | | | - DC
| DC-M1 - has knowledge of the basic concepts, structures and coherence. | | | | - BC
| The student can recognize the basic parts of a robot (sensors/actuators) | | | - DC
| DC-M2 - has insight in the basic concepts and methods. | | | | - BC
| The student understands the functionality of the different parts of the robot. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions. | | | | - BC
| The student can select the appropriate sensors for completing a given task. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs. | | | | - BC
| The student can integrate the given sensors/motors into a working robot. | - EC
| EC7 - The holder of the degree has specialist knowledge of and insight in principles and applications within the domains of computer technology and algorithms of programming languages, in which he/she can initiate, plan, critically analyse and create solid solutions with eye for data processing and implementation, with the help of simulation techniques or advanced tools, while being aware of potential mistakes, practical constraints and with attention to the topical technological developments. | | | - DC
| DC-M1 - has knowledge of the basic concepts, structures and coherence. | | | | - BC
| The student knows basic methods for control, motion planning, robot vision, and task planning. | | | - DC
| DC-M2 - has insight in the basic concepts and methods. | | | | - BC
| The student can design the software architecture for a robot. | | | | - BC
| The student understands the differences among methods, as well as the pros and cons of each method. | | | - DC
| DC-M3 - can recognize problems, plan activities and perform accordingly. | | | | - BC
| The student can identify bottlenecks and problems in the robot software. | | | - DC
| DC-M4 - can gather, measure or obtain information and refer to it correctly. | | | | - BC
| The student can measure the performance of each method and interpret the results. | | | - DC
| DC-M5 - can analyze problems, logically structure and interpret them. | | | | - BC
| The student can identify sources of bottlenecks or errors and plan activities to correct them. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions. | | | | - BC
| The student can select appropriate methods for communication among the software components of the robot. | | | | - BC
| The student is able to select appropriate methods and algorithms given the task. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs. | | | | - BC
| The student can implement software methods for component-based robot architectures. | | | | - BC
| The student can implement the appropriate methods and algorithms given the task. | | | - DC
| DC-M8 - can evaluate knowledge and skills critically to adjust own reasoning and course of action accordingly. | | | | - BC
| The student can evaluate the performance of the robot in a given task and adjust components/algorithms to improve it. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
This course focuses on bridging the gap between artificial intelligence and robotic systems. It will explore the basics of a robotic system (sensors, actuators, software etc.), and how artificial intelligence can be used to improve the autonomy of such robotic systems. Part of the course will focus on knowledge representation, reasoning, plannig. In addition, there will be a focus on how one goes from semantic knowledge representations, to actual software implementations that allow the robot to interact with the environment.
|
|
|
|
|
|
|
|
|
Application Lecture ✔
|
|
|
|
|
|
|
|
Demonstration ✔
|
|
|
|
Discussion/debate ✔
|
|
|
|
Exercises ✔
|
|
|
|
Homework ✔
|
|
|
|
Period 1 Credits 4,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
All material will be distributed through the electronic learning platform. |
|
|
|
|
|
1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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