Academic Skills Computational Science

Course manual 2024/2025

Course content

In this course, students read and discuss recent scientific papers, attend guest lectures by the Computational Science Lab researchers and visiting scientists,  learn the best practices and tools for computational science, and learn the basics of high-performance computing and advanced programming techniques for computational modelling.

Study materials

Literature

• Computational Science journals:  – Journal of Computational Science (Elsevier) – Computing in Science and Engineering (IEEE) – Other topical journals

Practical training material

• Computational Science tools, libraries, models and methods

Other

• Handouts, papers, and assignments are provided via Canvas

Objectives

• After a successful completion of the course, the students can: i) demonstrate the breadth of knowledge in Computational Science methods and applications;
• ii) describe the best practices in scientific research;
• iii) apply Computational Science tools in their research;
• iv) demonstrate critical thinking and inquisitive approach to reading literature and attending lectures;
• v) use advanced programming techniques for computational modelling.

Teaching methods

• Lecture
• Seminar
• Computer lab session/practical training

Attendance

This programme does not have requirements concerning attendance (Ter part B).

Assessment

• No marks, only pass/no pass with sufficient performance in all elements of the course in which at least 75% of Quizzes completed and all assignments submitted to pass the course.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Contact information

Coordinator

• dr. Valeria Krzhizhanovskaya