Seminars Computational Science

6 EC

Semester 1 & 2, period 1, 2, 4, 5

5284SECS6Y

Owner Master Computational Science (joint degree)
Coordinator dr. Valeria Krzhizhanovskaya
Part of Master Computational Science (Joint Degree),

Course manual 2022/2023

Course content

In the Seminars, students attend guest lectures by the Computational Science Lab researchers and visiting scientists, read and discuss recent scientific papers, give an oral presentation and provide peer-review to their classmates, learn the best practices and tools for computational science, learn the basics of high-performance computing and advanced programming techniques for computational modelling, and participate in a modelling hackathon. 

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, assignments are provided via Canvas

Objectives

  • After a successful completion of the course, the students can: demonstrate the breadth of knowledge in Computational Science methods and applications
  • give an oral presentation about Computational Science methods or applications
  • describe the best practices in scientific research
  • apply Computational Science tools in their research
  • demonstrate critical thinking and inquisitive approach to reading literature and attending lectures
  • use advanced programming techniques for computational modelling

Teaching methods

  • Lecture
  • Seminar
  • Presentation/symposium
  • Computer lab session/practical training

Attendance

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

Additional requirements for this course:

Attendance of at least 75% of the sessions

Assessment

Item and weight Details

Final grade

Total Attendance

Must be ≥ 21

Presentation slides, quiz questions & peer feedback

Must be ≥ 1

Hackathon+Ethics

Must be ≥ 1
  • No marks, only pass/no pass with sufficient performance in all elements of the course: 
  • Attendance of the seminars (at least 75%), quizzes, oral presentation, peer feedback, assignments, and modelling hackathon. 

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

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

  • dr. Valeria Krzhizhanovskaya