About the programme
Source: https://www.universiteitleiden.nl/en/education/study-programmes/master/computer-science/computer-science-and-education/about-the-programme Parent: https://www.universiteitleiden.nl/en/education/study-programmes/master/computer-science/computer-science-and-education
Computer Science and Education (MSc)
About the programme
The Computer Science and Education specialisation consists of 120 European Credit Transfer System (EC) points and consists of a computer science component (60 EC) and an education component (60 EC).
Programme overview
The curriculum of this master’s specialisation consists of a Computer Science component to be followed in the first year, and an Education component in the second year, offered by the Leiden Graduate School of Teaching. On top of the Education component, you can also participate in the World Teachers Programme.
Computer Science component (60 EC)
- Research Project in Computer Science (30 EC)
- Courses in correspondence with the research topic (30 EC)
Education component (60 EC, in Dutch)
- Education Courses (30 EC, in Dutch)
- Teaching and Practice (30 EC, in Dutch)
World Teaching Programme (60 EC, in Dutch and English)
- Education Courses (30 EC, partly in Dutch)
- International Teaching and Practice (30 EC, in English)
If you already have successfully completed the minor Education in your BSc programme, you only need 30 EC of the specific education modules. \ \ The education component can only be started in August/September or January/February after completion of the Computer Science modules of the programme.
Read more about the programme outline and courses.
Are you ready for this programme?
The Computer Science and Education programme is a research-oriented master programme and requires you to have the appropriate knowledge and skills before you start. The most important prior knowledge and skills can be summarised as follows:
- Good programming skills in C++ and/or Python
- Good knowledge of algorithms and data structures
- Basic understanding of artificial intelligence and data mining / machine learning
- Good academic reading and writing skills; proficient in LaTeX
- Excellent command of English, both in writing and speaking
- Independent and critical research attitude
If you doubt whether you meet these expectations and consider applying, contact our study advisor. Read the formal Admission requirements for additional information.
Educational methods
- Colloquium
- Lectures
- Individual papers
- Lab work
- Presentations
- Research
- Projects
- Seminars
- Work group
- Internship
- School practice
- Master's Thesis Research Project