3 ECTS credits
90 h study time

Offer 1 with catalog number 4023573DNR for all students in the 1st semester at a (D) Master - preliminary level.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Taught in
English
Faculty
Faculteit Ingenieurswetenschappen
Department
Electronics and Informatics
Educational team
Nikolaos Deligiannis (course titular)
Activities and contact hours

6 contact hours Lecture
8 contact hours Seminar, Exercises or Practicals
60 contact hours Independent or External Form of Study
Course Content

This course is designed to equip students with skills required to build a successful career in today’s applied computer science and engineering environments, including problem-solving, organization, teamwork, and active listening. The students will 1) learn how applied computer science, data science and artificial intelligence (AI) is applied in modern industry; 2) upgrade their soft skills by interacting in groups with industry experts and alumni; and 3) develop their writing and presentation skills by putting together and defending a work-plan -- in the form of a research proposal or statement of work -- related to applying computer science, data science and/or AI to address an industry related problem.

The course draws on a variety of teaching methods:

  • First, a set of lectures will be delivered by the teaching team and invited industry experts (including alumni) on 1) the role of applied computer science and scientists in modern industry and 2) the elements of a successful R&D proposal or statement of work, including aspects about consortium formation, writing and defending.
  • A practical part and a self-work part where:
    • Students work in groups to define relevant and contemporary research and / or development questions related to applied computer science, data science and AI, by researching various sources and interviewing industry or research expert (including alumni). The practical session includes a presentation per group on the results of the research and the R&D question.
    • Students write collaboratively and defend a proposal (research proposal or statement of work) in response to the R&D challenge.
Additional info

At the end of this course, the student will have developed a knowledge and understanding in how computer science, data science and AI can be applied in industry. The student will be able to formulate R&D questions and write a proposal or statement of work as well as assess such questions and proposals from peers. By working in a group towards preparing a proposal and presentation (as well as the evaluation of them) and through interactions with experts, the student will build soft skills necessary in today’s industrial and research environments.

Learning Outcomes

Learning outcomes

This course contributes to the following programme outcomes of the Master in Applied Computer Science:

 

MA_A: Knowledge oriented competence

 

1. The Master in Engineering Sciences has in-depth knowledge and understanding of exact sciences with the specificity of their application to engineering

5. The Master in Engineering Sciences can conceive, plan and execute a research project, based on an analysis of its objectives, existing knowledge and the relevant literature, with attention to innovation and valorization in industry and society

7. The Master in Engineering Sciences can present and defend results in a scientifically sound way, using contemporary communication tools, for a national as well as for an international professional or lay audience

8. The Master in Engineering Sciences can collaborate in a (multidisciplinary) team

11. The Master in Engineering Sciences can think critically about and evaluate projects, systems and processes, particularly when based on incomplete, contradictory and/or redundant information

 

MA_B:  Attitude

 

12. The Master in Engineering Sciences has a creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society

13. The Master in Engineering Sciences has a critical attitude towards one’s own results and those of others

14. The Master in Engineering Sciences has consciousness of the ethical, social, environmental and economic context of his/her work and strives for sustainable solutions to engineering problems including safety and quality assurance aspects

 

MA_C:  Specific competence

 

24. The Master in Applied Computer Science is able to manage complex multidisciplinary projects on end-to-end systems and, as a consequence, can take educated, well-researched decisions on the technologies involved

26. The Master in Applied Computer Science can apply his/her acquired knowledge and skills for designing smart city or digital health end-to-end dedicated systems.

27. The Master in Applied Computer Science is aware of and critical about the impact of ICT on society.

Grading

The final grade is composed based on the following categories:
Other Exam determines 100% of the final mark.

Within the Other Exam category, the following assignments need to be completed:

  • Presentation R&D question with a relative weight of 25 which comprises 25% of the final mark.

    Note: the evaluation of the presentation of the R&D question and in general the interactions with the industry/research expert
  • Written proposal with a relative weight of 40 which comprises 40% of the final mark.

    Note: the evaluation of the written proposal / statement of work, which contributes with 40% to the final grade
  • Oral defense proposal with a relative weight of 35 which comprises 35% of the final mark.

    Note: the oral defense of the proposal and the performance as jury, which contributes with 35% to the final grade

Additional info regarding evaluation

The final grade consists of three parts:

1) the evaluation of the presentation of the R&D question and in general the interactions with the industry/research expert, which contributes with 25% to the final grade;

2) the evaluation of the written proposal / statement of work, which contributes with 40% to the final grade; and

3) the oral defense of the proposal and the performance as jury, which contributes with 35% to the final grade.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Master in Applied Sciences and Engineering: Applied Computer Science: Standaard traject