| Language of instruction : English |
|
Sequentiality
|
| |
|
No sequentiality
|
| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | Master of Software Systems Engineering Technology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
|
| | | 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. | | | - DC
| DC-M2 - has insight in the basic concepts and methods. | | | - DC
| DC-M3 - can recognize problems, plan activities and perform accordingly. | | | - DC
| DC-M4 - can gather, measure or obtain information and refer to it correctly. | | | - DC
| DC-M5 - can analyze problems, logically structure and interpret them. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs. | - 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. | | | - DC
| DC-M3 - can recognize problems, plan activities and perform accordingly. | | | - DC
| DC-M5 - can analyze problems, logically structure and interpret them. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions. | | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs. | - EC
| EC4 - The Master of Software Engineering Technology has advanced knowledge and understanding of principles and applications of contemporary wireless and mobile communication networks, and in this domain, (s)he can autonomously initiate, plan, critically analyse and solve problems in a well-founded manner with an eye for data acquisition and implementation, and with the help of simulation techniques or advanced tools. [connected] | | | - DC
| DC-M5 - can analyze problems, logically structure and interpret them. | | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions.
| | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs.
| - 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.
| | | - DC
| DC-M2 - has insight in the basic concepts and methods.
| | | - DC
| DC-M3 - can recognize problems, plan activities and perform accordingly. | | | - DC
| DC-M4 - can gather, measure or obtain information and refer to it correctly.
| | | - DC
| DC-M5 - can analyze problems, logically structure and interpret them.
| | | - DC
| DC-M6 - can select methods and make calculated choices to solve problems or design solutions.
| | | - DC
| DC-M7 - can use selected methods and tools to implement solutions and designs.
| | | - DC
| DC-M8 - can evaluate knowledge and skills critically to adjust own reasoning and course of action accordingly.
|
|
| | 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 Toledo |
|
|
|
|
|
1 examination regulations art.1.3, section 4. |
| 2 examination regulations art.4.7, section 2. |
3 examination regulations art.2.2, section 3.
|
| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
|