Syllabus for Advanced Course on Topics in Scientific Computing I
Öppen fördjupningskurs i beräkningsvetenskap I
A revised version of the syllabus is available.
- 5 credits
- Course code: 1TD322
- Education cycle: Second cycle
Main field(s) of study and in-depth level:
Computational Science A1F,
Computer Science A1F
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
- G1N: has only upper-secondary level entry requirements
- G1F: has less than 60 credits in first-cycle course/s as entry requirements
- G1E: contains specially designed degree project for Higher Education Diploma
- G2F: has at least 60 credits in first-cycle course/s as entry requirements
- G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
- GXX: in-depth level of the course cannot be classified
- A1N: has only first-cycle course/s as entry requirements
- A1F: has second-cycle course/s as entry requirements
- A1E: contains degree project for Master of Arts/Master of Science (60 credits)
- A2E: contains degree project for Master of Arts/Master of Science (120 credits)
- AXX: in-depth level of the course cannot be classified
- Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Established: 2011-03-10
- Established by: The Faculty Board of Science and Technology
- Revised: 2011-03-10
- Revised by: The Faculty Board of Science and Technology
- Applies from: Spring 2011
At least 120 credits of which at least 30 credits in mathematics. In addition 20 credits Computer Science, where Scientific Computing III or Scientific Computing, bridging course or the equivalent must be included.
- Responsible department: Department of Information Technology
The overall aim of this course is to offer an opportunity to deepen the knowledge in scientific computing, in an area not covered by ordinary courses. It can be done through studies of research papers, text books or projects. Alternatively it can be done by participating in a PhD-level course. In the former case, the learning outcomes are:
To pass, the student should be able to
- assimilate new content on advanced level through a substantial proportion of self-studies;
- summarise and assess the content of the chosen area in scientific computing;
- identify, obtain and use core knowledge related to the task;
- integrate, generalise and combine prior knowledge in computational science
In the case when the course content is a PhD-level course, the student must fulfil the learning outcomes of the PhD-level course.
The exact content is decided upon each individual course instance. The content must be on advanced level in one area within scientific computing. Here, we consider scientific computing in a broad sense; applications in Physics, Chemistry, Biology etc. are well suited under the condition that they have a computational focus.
Decided upon on each course instance.
A suitable exam is decided by examiner on each course instance. Types of examinations are written tests, oral examination of a research paper or a book and/or implementations and studies of numerical methods and its properties.
The course content (the title of the course topic) and examiner is registered in UPPDOK. This course differs from 1TD326 Advanced Course on Topics in Scientific Computing II, 10 credits only in extent and not in level or depth. Both courses can be included in a degree provided that the content is not overlapping.
- Latest syllabus (applies from Autumn 2023)
- Previous syllabus (applies from Autumn 2022)
- Previous syllabus (applies from Spring 2019)
- Previous syllabus (applies from Autumn 2012, version 2)
- Previous syllabus (applies from Autumn 2012, version 1)
- Previous syllabus (applies from Spring 2011)
- Previous syllabus (applies from Autumn 2010)
The reading list is missing. For further information, please contact the responsible department.