Course manual 2023/2024

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

Learning activities

Activity	Hours
Hoorcollege	28
Self study	140
Total	168	(6 EC x 28 uur)

Attendance

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

Additional requirements for this course:

The students should complete at least 75% of Quizzes (after the lectures) and submit all assignments (after the tutorials) to pass the course.

Assessment

Item and weight	Details
Final grade

No marks, only pass/no pass with sufficient performance in all elements of the course in which at least 75% of Quizzes (after the lectures) completed and all assignments (after the tutorials) 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

Course structure

Week	Topic	Activity
1	Seminars Goals, Plans, Schedule	Lecture; Quiz
2	Environmental Complexity for Human Outcomes	Lecture; Quiz
3	Tutorial Session on 'Tools for Computational Scientists'	Practical Training; Assignment
4	Computational Chemistry	Lecture; Quiz
5	Computational Biology	Lecture; Quiz
6	a) Purely Academic Theatre b) Responsible Use of Generative Artificial Intelligent (GenAI)	a) Theatre play recording; Assignment (at home) b) Canvas eModule; Quiz (at home)
7	Multilayer Disease Network via Multipartite Projections	Lecture; Quiz
8	EXAM WEEK (NO LECTURE)
9	Tutorial Session on 'Julia programming'	Practical Training; Assignment
10	a) Introduction on the Finite Element Method b) Simulating Societies: An ABM Example Application	Lecture; Quiz
11	Tutorial Session on 'High Performance Computing (HPC)'	Practical Training; Assignment
12	Statistical Inference by A Physicist	Lecture; Quiz
13	Computational Finance	Lecture; Quiz
14	Society as A Complex Adaptive System	Lecture; Quiz

Owner	Master Computational Science (joint degree)
Coordinator	R.M. Hilman
Part of	Master Computational Science (Joint Degree),

Academic Skills Computational Science