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:

    First cycle

    • 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

    Second cycle

    • 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
  • Entry requirements:

    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

Learning outcomes

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.

Content

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.

Instruction

Decided upon on each course instance.

Assessment

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.

Other directives

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.

Syllabus Revisions

Reading list

The reading list is missing. For further information, please contact the responsible department.

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